Look at this.
We could have built a new Krypton
...in this squalor.
But you chose the humans over us.
I exist
only to protect Krypton.
That is the sole purpose for which I was born.
And every action I take
no matter how violent
or how cruel...
...is for the greater good
of my people.
And now...
I have no people.
My soul
that is what you have taken
from me.
I'm going to make them suffer, Kal.
These humans you've adopted, I will take them all from you...
- ...one by one. - You're a monster, Zod...
...and I'm gonna stop you.
There's only
one way this ends, Kal.
Either you die
...or I do.
I was bred to be a warrior, Kal.
Trained my entire life
to master my senses.
Where did you train? On a farm?
For more infomation >> Superman vs Zod Final Fight (Part 1) | Man of Steel (2013) Movie Clip - Duration: 4:40.-------------------------------------------
#BitenlerVideolar👩🏻🌾 Sevdiklerim ve Sevmediklerim / #Domestos💎#Lancome💡#Temizlik👈# - Duration: 15:03.
For more infomation >> #BitenlerVideolar👩🏻🌾 Sevdiklerim ve Sevmediklerim / #Domestos💎#Lancome💡#Temizlik👈# - Duration: 15:03. -------------------------------------------
Superman vs Zod Final Fight (Part 2) | Man of Steel (2013) Movie Clip - Duration: 3:47.
If you love these people so much...
...you can mourn for them.
Don't do this!
Stop!
Stop!
Never.
-------------------------------------------
DeltaRune Demo - Duration: 38:26.
For more infomation >> DeltaRune Demo - Duration: 38:26. -------------------------------------------
NEFES VEDAT'A DÖNÜYOR | SEN ANLAT KARADENİZ 29. BÖLÜM FRAGMANI - Duration: 2:22.
For more infomation >> NEFES VEDAT'A DÖNÜYOR | SEN ANLAT KARADENİZ 29. BÖLÜM FRAGMANI - Duration: 2:22. -------------------------------------------
Damage done by thrown beer cans at Red Sox parade - Duration: 1:03.
For more infomation >> Damage done by thrown beer cans at Red Sox parade - Duration: 1:03. -------------------------------------------
Noam Dar gives a standing ovation to the Cambridge crowd at NXT UK: Exclusive, Oct. 31, 2018 - Duration: 1:20.
[APPLAUSE]
[MUSIC]
-------------------------------------------
SIAMÉS - "Mr. FEAR" [Official Animated Music Video] - Duration: 4:34.
HELLO, MY NAME IS MR. FEAR
I WISH I HAD A FASTER THERAPY
I'VE COME TO MIND CONTROL YOUR NEEDS
TONIGHT I'M GONNA STAR ALL OF YOUR LEADS
YOU KNOW I'LL NEVER DISAPPEAR
NOW GET ME OUT OF HERE
JUST TRUST IN ME MY DEAR
NO CURE IS COMING NEAR...
HOW LONG YOU'LL CALL ME INSINCERE?
I'M NOT HERE TO FULFILL YOUR PARODY
HOW COME MY SONG BECOME UNREAL?
YOU NEVER UNDERSTAND MY MELODIES
YOU KNOW I'LL NEVER DISAPPEAR
NOW GET ME OUT OF HERE
JUST TRUST IN ME MY DEAR
NO CURE IS COMING YOU KNOW
I'LL NEVER DISAPPEAR
NOW GET US OUT OF HERE
DON'T FIGHT WITH ME MY DEAR
WHY CAN'T I BE IN HERE?
CAUSE YOU MAKE ME FEEL
LIKE I'M SO ALONE
I KNOW IS NOT REAL
BUT IT'S IN MY SOUL
AND I JUST CAN TRY TO FACE
THE DARK INSIDE MY HEAD
YOU KNOW I'LL NEVER DISAPPEAR
NOW GET ME OUT OF HERE
JUST TRUST IN ME MY DEAR
NO CURE IS COMING YOU KNOW
I'LL NEVER DISAPPEAR
NOW GET US OUT OF HERE
DON'T TRUST IN ME MY DEAR
WHAT CURE IS COMING NEAR...?
-------------------------------------------
OVERNIGHT in World's Most HAUNTED FOREST | Hoia Baciu Forest Romania - Part 2 - Duration: 28:53.
...We're starting to hear our first bump in the night...
...voices, giggles, screams are reported to be very common coming out of the forest...
Hey guys. thank you for tuning in to Amy's Crypt and happy Halloween! I am
really excited for tonight. This is my big finale to my October long haunted
Romania series and Ihave saved the best until last... overnight in the World's Most
Haunted Forest Hoia Baciu. I'm really excited. I've got lots of cool things
planned. we're going to be camping here. I'm gonna have a fire. I'm going to be
telling ghost stories. I'm gonna do some paranormal investigating and I have some
Halloween Candy. If you guys need to catch up on part one
I'll link that below but I think it's time to get spooky. Alright guys we are
in the middle of the dead zone. this is also our base camp.
okay so it's actually getting really chilly now. the sun's starting to set. It's
gonna be a pretty cold night but I'm actually really excited for it. we were
hoping we've got enough clothes, sleeping bags, firewood to keep us warm throughout
the night. but we're really excited to camp here and one of the things that I
really really want to get out of tonight is I want to see lights in the forest.
That is something that this area is known for and I just really would love
to see that. love to see what's on the other side of it as well,what is
creating these lights that so many people claim to have seen and even
captured on camera. so as the Sun Goes Down we'll probably start doing a couple of
paranormal experiments. obviously gonna try spirit box, EVPs will
be really cool around here and disembodied voices giggles, screams
are reported to be very common coming out of the forest. it's kind of creepy to think
that we are sleeping in this area which is basically a perfect circle in the
middle of the forest. nothing grows here and there's no reason why it shouldn't
grow. so it's a bit of a mystery this is also where a lot of the paranormal
activity is set to Center. UFO sightings have been here and people have
even been attacked here and I just feel like we're camping directly in the
center of this clearing. we can be watched by anyone in the woods and we
can't see them. so it's kind of nerve-wracking and I feel a little
vulnerable sitting here in the middle waiting for it to go dark. I wouldn't
want to camp anywhere else here. I just feel like if we're gonna see or experience
something it's probably gonna be here. crossing my fingers for Halloween...
alright guys it's finally dark and we're starting to hear our first bump in the
night. so there's a lot of noise coming from the forest around us. but it's very
creepy out here. just surrounded by the World's Most Haunted Forest in the
middle of the night, so it's gonna be a long night that's quite freaky
I'm hearing a lot of noises
coming from the forest.
its quite freaky.
It's probably just animals. But I hear like tree branches snapping and falling. there's
also a plane going overhead I can hear. yea I can hear a plane. and I've heard a
few planes go over and seen them. no UFOs yet though. it's cold.
it's so cold isn't it? ok so we just heard a very bizarre noise coming from
the forest. I'm hoping that the speaker on my camera recorded it but it almost
sounded like a high-pitched cough and it occurred multiple times.
it could be an animal but it was...
...did you hear that?
Yeah. There's something over there.
It almost sounded like it ran. Yeah. I'm sure its probably an animal. Ok so I was telling Jarrad before I would love to
see a UFO, a ghost or anything really unexplainable, but my biggest fear out
here is the living. I'm so scared that someone's gonna stumble across us like
out here, and I'm here for the paranormal! not to be harassed by humans.
Alright guys this is just a plane flying overhead. you can see the lights clearly
on the camera. it is not paranormal or UFO. it's definitely identified. One
thing that is weird and it's either a bug with app or paranormal
but my phone's battery has just drained from 49% to 14% in about 10
minutes. I don't know if you can see that on
camera. it's actually something that has been reported in the forest is
electrical disturbances or electrical equipment just draining of battery. yeah.
like this was a sudden. this was fully charged when we left today and I had it
off all day. we literally just turned it on. And... I am actually
seeing a light through there. where? and over there. I'm seeing like lights.
I can't see. like distant, like someone's walking through with a torch, but,
seriously right in there. I'm not S******* you. do you think someone's coming? I do.
I'm gonna light the fire.
okay in this next clip we picked up what sounds like distant violin music. this
was not audible to us at the time. let me know in the comments below what you
think it may be.
Jared just said that he saw lights in the forest? yeah. which is a common thing.
I seen these lights through the trees sort of like the light that's shining on me.
a white light, maybe like a torch. It was very small and it was either
flashing on and off or moving through the trees. it was in the distance. I
really would say I mean... maybe there's other people here?
Amy is now also claimed to see a light. hang on let me get down...
Really low to the ground. just through the bushes here. it wasn't heaps bright like
a spotlight. There was a light out there like a white
blue light. this is the same area and direction you saw the light, right? yeah.
it's odd and the other lights they're definitely not stars or the moon. They're
much lower, lower to the ground. yeah. Alright let's see if I can capture this light.
Wait! Oh I think I'll got one! yes! I can see one! there! okay that's the light! that's
what we're seeing! And we are seeing them all around us!
and then they go away. There it is again. I can see it now. Ok that's
really cool because this is exactly why I came out here and what I want to see.
there's been a lot of reports of people siting light anomalies, unexplained light
activity. all right guys we're gonna venture into the forest now for a bit/
we're gonna head towards most of the sound activity that we've had and
the lights and see if we can pick up on anything or debunk what we've seen. yeah
follow me! Jarrad can you see? Yep. Can you film some of these?
So I definitely think those lights that we've been seeing
maybe streetlights from the city in the distance. What do you think? mmm maybe. so
weird that their like all around and seeing more of those lights in the distance.
I reckon maybe it's the town. I think that they're from the city. Maybe that's what people see then?
so cluj-napoca is quite a big city and it's very close by to the forest. closer
than a lot of the TV shows or things that you've seen on the internet may
suggest. yeah we're watching a ghost show last night and they made it seem like a
big deal getting to this forest and, I mean, it is, it was hard to get to but
we not here in a taxi! yeah! it's not in the middle of nowhere. like it's
right next to a big city.
okay guys so I want to do an EVP session and when I do reach out in places like
this I tend to prefer to do so in the language of that particular country. and
I think if I reach out and there are spirits in this forest they're most
likely to interact if I talk to them in Romanian which I do not speak. I don't
have my phone on me right now cuz I left it back at camp like a dingbat so what I
think that we should do is maybe just remain silent for a little while and see
if we can hear anything strange.
that's our fire crackling in the distance. no it's not. Our fire is behind me. No
that sound came from behind you. I thought if it came from behind you?
that's the thing these sounds sound like they are all around us.
That is definitely behind you. See I swear to god that's behind you.
I think sound echoes in this place and carries so when there's an animal over
here and it treads on a stick and it breaks we hear it but we actually can't
tell where it's coming from, and particularly when you're in the middle
of that circle it just sounds like there's noise all around you. just
surrounding you. all right let's listen.
sounds like the Blair Witch Project when they hear stones banging in the distance
It keeps going.
That's definitely a F***** animal, surely.
okay so out here a lot of apparitions have been seen that look as if they are
people, but they're made of black shadow there's also common report...
there's definitely somebody walking in there. must be a deer all right but as I
was saying a lot of people have experienced and reported suddenly
forming black mist just out of nowhere and that usually coincides with
apparition sightings as well. so I haven't seen anything similar to that or
experienced anything like that but I can totally just imagine it happening out
here. because particularly at night when it is this dark it is very creepy.
so Jarrad can you just repeat what you were telling me just before? about the
thing? yeah. since about 4 o'clock today I've been
feeling like, tight chested, like anxious. I'm nervous about something and almost
like getting heart palpitations as well. a lot of people have also
suddenly become ill, migraines, headaches nausea, vomiting - but I also feel like so at
four o'clock that's kind of when I finished moving that wood I actually felt honestly
like I was working too hard and I wasn't drinking enough or eating enough.
I only ate half my lunch. so I don't know what it is but I feel
like shit. like really like worn and like what my chest is really weak. I'm getting
like palpitations every now and then. we'll just tell me if that keeps up or
you feel anything else strange because I want to document that just in case it
means something.
Jarrad watches a lot space programs about UFOs, aliens in the universe - what do you
think about all the UFO sightings in this area Jarrad? do you think their true?
why do you think there's so many? in general I feel like like I
believe in aliens and that. like I feel like they're out there. the universe is
too vast and expansive to not have other life forms. but I think it's so vast and
expensive that the odds of them coming into contact with us while humans are
still around is very small. I don't think they've visited us at all. so do you have
an explanation as to why you think this spot specifically there's been so many
sightings and there's even been some photographed?
I think UFOs as in unidentified flying objects could exist. I don't know maybe
they're military or maybe people just hear the stories that other people heard and
seem a photo here and then people come out here and their mind tells them
what they want to hear or what they want to see, you know? by the way that's a
plane, not a UFO. I didn't hear it. It came from right behind me. this place is
weird and by the way we don't have a tent or anything. we are sleeping under
the stars. and I mean apart from not wanting to spend the money to buy a tent
I also want to sleep under stars so if anything does fly over us or any make
lights appear we have more chance of seeing them and capturing them on film. so
I'm setting up my spirit box now I think because we are camping out in the dead
zone, this clearing here is so notorious for paranormal activity occurring.
Oh it's so scary. alright guys this is my spirit box box session in Hoia Baciu Forest.
in the dead zone. by the way I don't speak Romanian. I'm gonna do my
best to reach out in Romanian. laugh if you will.
Ok, I'm getting a lot of voices through. I can't understand them.
I'm gonna stop this there. there is a lot of voices coming through.
it is difficult and challenging investigating these places in countries
that are foreign to me where I don't speak the language. if you do speak
Romanian or you noticed any words or phrases come through that kind of made
sense to what I was attempting to ask in Romanian I would love and really
appreciate if you could leave me a comment and let me know. alright guys
we're gonna walk back into a different part of the forest.
this one is an area where both Jarrad and I heard - if we had to describe it what
sounded like an old lady crying out - we're gonna proceed with
an EVP session for now.
I just heard footsteps over there...
Oo it came from behind you. I swear that came from that way. no to me
it came from behind you. to me it came from behind you. This forest is weird.
You know what is scary to think of? with all the stories of people getting
lost in here and going missing for years on end and then reappearing years later
with no recollection of what happened, imagine if we are lost right now.
and this is day one? yeah. really like we've been gone for five
years. yeah that would be creep.y and we don't even know everyone else outside the
forest is like looking for us. do you know what I mean? yeah. it's creepy.
so I've done an EVP. I'm gonna have to review the footage later and see if
we pick up on anything.
now since it is so creepy I thought I would lighten the mood a little bit and
also since you guys are watching this on Halloween we have some Halloween candies
to sample similar to what we did at Dracula's castle. we did a little twist
this time though where I picked out some candy for Jarrad and he picked out some
candy for me. they're all foreign and we have no idea what we're going to be
sampling. so let's find out what we got each other. all right Amy's turn
for her first chocolate. I am really excited. all right so the first one I chose for you is this one. for
everyone at home. Mmm. It tastes like, not the best quality chocolate.
I am gonna give Jarrad his first treat, which he doesn't actually
know what it is. it is this one here.Here you go. Joe Extra Extra Large?
It's not that large though, really. Mmm Chocolate covered wafers. Good quality, too.
Ok time for Amy's last chocolate. We have...
Just what I always wanted! Wanted nuts!!!
It's hard to open with Gloves. Oo.. I lost a nut.
Is it good? Almost broke all my teeth from it but
it's good. all right are you ready for your last treat? yep. this one is the best
one. you're gonna also hard. so when I saw this I couldn't resist buying
it for Jarrad... A bum bar? Wow. It looks like it came
out of someone's bum. Show me.
alright guys it's getting really late and it is freezing cold so we're gonna
jump into our sleeping bags and call it a night.
We have done a fair bit of investigating and just found this place to be pretty
creepy and interesting. I'm probably just gonna lay here with my eyes open all
night looking out for strange lights and whatnot. I can try and capture that on
camera if I do see anything. but we will try and get some sleep and if we survive
the night you'll see us again in the morning.
hi guys we managed to survive the night, just waiting for the Sun to fully come
up now and we are packing up the campsite. it was freezing cold and our
sleeping bag got really wet from condensation. thank you guys so much for
watching and have a happy Halloween. if you did like this video please
remember to Like comment and subscribe that way I can keep taking you on these
spooky adventures. if you're looking for a bit more reading on a haunted places
head to AmysCrypt.com remember guys until next time stay
spooky.
This is where Jarrad's head was all night. He slept on a peice of poo. *laughs*
Idiot.
-------------------------------------------
This Pirates Of The Caribbean Actress Is Gorgeous In Real Life - Duration: 3:48.
If you're familiar with the Pirates of the Caribbean franchise then you'll no doubt recognize
voodoo enchantress Tia Dalma, but what you might not know is that the woman beneath all
the dreads and makeup is just as alluring as the character she plays.
British actress Naomie Harris made her exciting debut as Dalma in 2006's Dead Man's Chest,
but the story of her life pre-Pirates is equally as interesting.
From her humble beginnings to her arrival in Hollywood, here's a look at the life and
career of the real Tia Dalma, the stunning Naomie Harris.
Teenage novelist
Early on in Harris' life, it became clear that she had a talent for writing as well
as performing.
By the time she was 13 she had completed an entire novel, a fish out of water story inspired
by her upbringing in one of London's less-desirable neighborhoods.
As Harris told The Guardian,
"It was about a middle-class girl whose parents get taken ill and she has to go and live on
a council estate with her aunt.
It was about the escapades she gets into and the culture shock, being from a very middle-class
background and ending up on a council estate."
Cambridge connections
Naomie Harris made her TV debut at the age of nine, but didn't come to the attention
of wider audiences until her mid-20s.
In 2002, she starred as Clara in the British miniseries White Teeth, which was well-received
on both sides of the Atlantic.
She seemed completely at ease with the source material, partly because she went to school
with the woman who wrote it.
The novel upon which the show was based was penned by Zadie Smith, who started at Cambridge
University the same year as Harris.
In an interview with The Telegraph, Harris said,
"She was cool, I was nerdy."
The big break
Naomie Harris marked herself out with her performance in White Teeth, showcasing raw
talent that director Danny Boyle was eager to refine.
In 2002, Harris put in a star turn opposite Cillian Murphy in Boyle's gritty, London-set
zombie apocalypse flick, 28 Days Later.
Harris told Digital Spy,
"[He] really started my career for me, I'm very grateful to Danny Boyle."
The first Bond woman
Harris debuted her version of the iconic Miss Moneypenny in 2012's Skyfall, the twenty-third
film in the James Bond franchise.
Speaking to The Telegraph, she explained how she helped redefine the Bond girl.
The actress revealed how she'd been asked to present an award at the BAFTAs, though
she took issue with what she was asked to read.
Harris was expected to refer to herself as a Bond girl, which wasn't going to fly - so
she decided to change it to "Bond woman."
"I've got some new information."
Moonlight moments
2017 was a huge year for Harris, whose performance as drug addict Paula in the Oscar-winning
Moonlight ensured she was kept busy over awards season.
She was nominated for Best Supporting Actress at the Oscars, Golden Globes and the BAFTAs,
and while she didn't end up winning, just having a seat at the table meant everyone
now knew her name.
Amazingly, Harris almost passed on the critically-acclaimed role because Paula's world was just so far
removed from her own.
Her performance is all the more amazing when you consider the fact that she's practically
teetotal in real life.
Harris told RogerEbert.com,
"I'm someone who's very clean-living.
I don't drink, I don't smoke."
Officer of the Order
She may have lost out on the highest honor in Hollywood when Viola Davis beat her to
the Oscar podium in 2017, but Naomie Harris was honored by her country for services to
drama that same year when the Queen personally made her an Officer of the Order of the British
Empire.
Speaking to the BBC, Harris explained why the award was so important to her:
"As a black actress from the background I came from, I think it's incredibly important.
I'm absolutely thrilled to have my work recognized in this way."
The future
We won't be seeing Harris in 2019, but we'll be hearing her.
Harris is voicing the part of Nisha in Mowgli, directed by Andy Serkis.
She claimed she'd "cleared her diary" for the upcoming Bond 25 during her appearance
on The Graham Norton Show, but she doesn't appear to have anything else going on in terms
of acting.
That doesn't mean she isn't going to be busy, however.
When she spoke to Vogue in January 2018, Harris revealed that she was working with the Intermission
Youth Theatre, a year-long drama program for London's inner-city communities.
With this program, Harris hopes to help educate the next generation of performers on how to
survive in showbusiness.
-------------------------------------------
Supervised Machine Learning: Crash Course Statistics #36 - Duration: 11:51.
Hi, I'm Adriene Hill, and welcome back to Crash Course Statistics. We've covered a
lot of statistical models, from the matched pairs t-test to linear regression. And for
the most part, we've used them to model data that we already have so we can make inferences
about it.
But sometimes we want to predict future data. A model that predicts whether someone will
default on their loan could be very helpful to a bank employee. They're probably not
writing scientific papers about why people default on loans, but they do care about accurately
predicting who will.
Many types of Machine Learning (ML) do just that: build models to predict future outcomes.
And this field has exploded over the past few decades. Supervised Machine Learning takes
data that already has a correct answer, like images that have been labeled as "cat"
or "not a cat", or the current salary of a company's CEO, and tries to learn how
to predict it. It's supervised because we can tell the model what it got wrong.
It's called Machine Learning because instead of following strict rules and instructions
from humans, the computers (or machines) learn how to do things from data.
Today, we'll briefly cover a few types of supervised Machine Learning models, logistic
regression, Linear Discriminant Analysis, and K Nearest Neighbors.
Intro
Say you own a microloan company. Your goal is to give short term, low interest loans
to people around the world, so they can invest in their small businesses. You have everyone
fill out an application that asks them to specify things like their age, sex, annual
income, and the number of years they've been in business.
The microloan is not a donation, the recipient is supposed to pay it back. So you need to
figure out who is most likely to do that.
During the early days of your company, you reviewed each application by hand and made
that decision based on personal experience of who was likely to pay back the loan.
But now you have more money and applicants than you could possibly handle. You need a
model--or algorithm--to help you make these decisions efficiently.
Logistic regression is a simple twist on linear regression. It gets its name from the fact
that it is a regression that predicts what's called the log odds of an event occuring.
While log odds can be difficult, once we have them, we can use some quick calculations to
turn them into probabilities, which are a lot easier to work with. We can use these
probabilities to predict whether an individual will default on their loan.
Usually the cutoff is 50%. If someone is less than 50% likely to default on their loan,
we'll predict that they'll pay it off. Otherwise, we'll predict that they won't
pay off their loan.
We need to be able to test whether our model will be good at predicting data it's never
seen before. Data it doesn't have the correct answer for. So we need to pretend that some
of our data is "future" data for which we don't know the outcome.
One simple way to do that is to split your data into two parts.
The first portion of our data, called the training set, will be the data that we use
to create--or train--our model. The other portion, called the testing set, is the data
we're pretending is from the future. We don't use it to train our model.
Instead, to test how well our model works, we withhold the outcomes of the test set so
that the model doesn't know whether someone paid off their loan or not, and ask it to
make a prediction.
Then, we can compare these with the real outcomes that we ignored before.
We can do this using a what's called a Confusion Matrix. A Confusion Matrix is a chart that
tells us what actually happened--whether a person paid back a loan--and what the model
predicted would happen.
The diagonals of this matrix are times when the model got it right. Cases where the model
correctly predicted that the person will default on the loan is called a True Positive. "True"
because it got it right. "Positive" because the person defaulted on their loan.
Cases where the model correctly predicted that a person will pay back the loan are called
True Negatives. Again "true" because it made the correct prediction, and "negative"
because the person did not default.
Cases where the model was wrong are called False Negatives--if the model thought that
they would not default--and False Positives--if the model thought they would default.
Using current data and pretending it was future data allows us to see how this model performed
with data it had never seen before.
One simple way to measure how well the model did is to calculate its accuracy. Accuracy
is the total number of correct classifications--Our True Positives and True Negatives--divided
by the total number of cases. It's the percent of cases our model got correct.
Accuracy is important. But it's also pretty simplistic. It doesn't take into account
the fact that in different situations, we might care more about some mistakes than others.
We won't touch on other methods of measuring a model's accuracy here, but it's important
to recognize that in many situations, we want information above and beyond just an accuracy
percentage.
Logistic regression isn't the only way predict the future. Another common model is Linear
Discriminant Analysis or LDA for short. LDA uses Bayes' Theorem in order to help us
make predictions about data.
Let's say we wanna predict whether someone would get into our local state college based
on their high school GPA. The red dots represent people who did not
get in, green are people who did.
If we make a couple of assumptions, we can estimate the GPA distributions of people who
did, and did not get their acceptance letter.
If we find a new student who wants to know if they will get in to your local state school,
we use Bayes Rule and these distributions to calculate the probability of getting in
or not.
LDA just asks, "Which category is more likely?" If we draw a vertical line at their GPA, whichever
distribution has a higher value at that line is the group we'd guess.
Since this student, Analisa has a 3.2 GPA, we'd predict that she DOES get in. Since
it's more likely under the "got in" distribution.
But we all know that GPA isn't everything. What if we looked at SAT Scores as well.
Looking at the distributions of both GPA and SAT scores together can get a little more
complicated. And this is where LDA becomes really helpful.
We want to create a score, we'll call it Score X, that's a linear combination of
GPA and SAT scores. Something like this: We, or rather the computer, want to make it
so that the Score X value of the admitted students is as different as possible from
the Score X value of the people who weren't admitted.
This special way of combining variables to make a score that maximally separates the
two groups is what makes LDA really special.
So, Score X is a pretty good indicator of whether or not a student got in. AND that's
just one number that we have to keep track of, instead of two: GPA and SAT score.
For this sample, my computer told me that this is the correct formula:
Which means we can take the scatter plot of both GPA and SAT score and change it into
a one-dimensional graph of just Score X.
Then we can plot the distributions and use Bayes Rule to predict whether a new student,
Brad, is going to get into this school.
Brad's Score X is 8, so we predict that he won't get in, since with a score X of
8, it's more likely that you won't get in than that you will.
Creating a score like Score X can simplify things a lot. Here, we looked at two variables,
which we could have easily graphed. But, that's not the case if we have 100 variables for
each student. Trust me, you don't want your college admissions counselor making admissions
decisions based on a graph like that.
Using fewer numbers also means that on average, the computer can do faster calculations. So
if 5 million potential students ask you to predict whether they get in, using LDA to
simplify will speed things up.
Reducing the number of variables we have to deal with is called Dimensionality Reduction,
and it's really important in the world of "Big Data". It makes working with millions
of data points, each with thousands of variables, possible.
That's often the kind of data that companies like Google and Amazon have.
The last machine learning model we'll talk about is K-Nearest Neighbors.
K-Nearest Neighbors...or KNN for short...relies on the idea that data points will be similar
to other data points that are near it.
For example, let's plot the height and weight of a group of Golden Retrievers, and a group
of Huskies:
If someone tells us a height and weight for a dog--named Chase--whose breed we don't
know...we could plot it on our graph.
The four points closest to Chase are Golden Retrievers, so we would guess he's a Golden
Retriever.
That's the basic idea behind K-Nearest Neighbors! Whichever category--in this case dog breed--has
the more data points near our new data point is the category we pick.
In practice it is a tiny bit more complicated than that. One thing we need to do is decide
how many "neighboring" data points to look at.
The K in KNN is a variable representing the number of neighbors we'll look at for each
point--or dog--we want to classify.
When we wanted to know whether Chase was a Husky or a Golden Retriever, we looked at
the 4 closest data points. So K equals 4. But we can set K to be any number.
We could look at the 1 nearest neighbor. Or 15 nearest neighbors. As K changes, our classifications
can change. These graphs show how points in each area of the graph would be classified.
There are many ways to choose which k to use. One way is to split your data into two groups,
a training set and a test set. I'm going to take 20% of the data, and ignore
it for now.
Then I'm going to take the other 80% of the data and use it to train a KNN classifier.
A classifier basically just predicts which group something will be in. It classifies
it. We'll build it using k equals 5.
And we get this result: Where blue means Golden Retriever. And red means Husky.
As you can see, the boundaries between classes don't have to be one straight line. That's
one benefit of KNN. It can fit all kinds of data.
Now that we have trained our classifier using 80% of the data, we can test it using the
other 20%. We'll ask it to predict the classes of each of the data points in this 20% test
set. And again, we can calculate an accuracy score. This model has 66.25% accuracy. But
we can also try out other K's and pick the one that has the best accuracy.
It looks like using a k of 50 hits the sweet spot for us. Since the model with k equals
50 has the highest accuracy of predicting Husky vs. Golden Retriever. So, if we want
to build a KNN classifier to predict the breed of unknown dogs, we'd start with a K of
50.
Choosing model parameters--variables like k that can be different numbers--can be done
in much more complex ways than we showed here, or could be done using information about the
specific data set you're working with . We not going to get into alternative methods
now, but if you're ever going to build models for real, you should look it up.
Machine Learning focuses a lot on prediction. Instead of just accurately describing our
current data, we want it to pretty accurately predict future data.
And these days, data is BIG. By one estimate, we produce 2.5 QUINTILLION bytes of data per
day. And supervised machine learning can help us harness the strength of that data.
We can teach models or rather have the models teach themselves how to best distinguish between
groups like will pay off a loan and those that won't. Or people who will love watching
the new season of The Good Place `and those that won't.
We're affected by these models all the time. From online shopping, to streaming a new show
on Hulu, to a new song recommendation on Spotify. Machine learning affects our lives everyday.
And it doesn't always make it better we'll get to that. Thanks for watching. I'll see you next time.
-------------------------------------------
Maquiagem Simples Para O Halloween | Sofia Vallin - Duration: 12:33.
For more infomation >> Maquiagem Simples Para O Halloween | Sofia Vallin - Duration: 12:33. -------------------------------------------
КАПИТАН МАРВЕЛ Странный Трейлер | ВЕСЁЛАЯ ПАРОДИЯ от Aldo Jones'а - Duration: 4:08.
BLOCKBUSTER VIDEO - WE REFUSED TO BUY NETFLIX, YOU KNOW?
Hello, welcome to Blockbuster.
Can I help you find something?
War is a universal language.
Oh. Oh, I get it.
Video store are so old they have ghosts in them
Ok, thanks, I get it but you are wrong.
I know renegade soldier when I see one.
Never occurred to me that one might come from above.
Nice Cap, Cap!
Actually, I'm still alive!
Space invasion.
How did you do that, How did you go invisible?
Big car chase.
Truth be told I was ready to hang it up...
'til I met you today.
I hate to shatter your ego, but this ain't the first time I've had a gun pointed at me.
Ah, ah, ah.
What do they call a Whopper?
WHY SO SERIOUS?
It's hard to explain
I keep having these memories.
I see flashes.
There's only one Captain, Ma'am.
Stay down.
I think I had a life here...
but I can't tell if it's real.
We have no idea what threats are out there.
We can't do this alone.
We need you.
SEND NUDES.
You're not the Batman, get out!
I'm not what you think I am
My name is Jeff.
-------------------------------------------
Lawyer Reviews Laws Broken In Classic Love Scenes - Duration: 11:46.
For more infomation >> Lawyer Reviews Laws Broken In Classic Love Scenes - Duration: 11:46. -------------------------------------------
How Eye Control empowers people with disabilities - Duration: 2:47.
>> Hi. I'm here with Jon Campbell
from the Microsoft Enable team.
And Jon, today, we're going to talk about
Eye Control and what's coming next.
Do you want to tell us a little bit about it?
>> So, people living with ALS, they lose their ability to move.
But they can still use their eyes.
So, Steve Gleason contacted Microsoft
and was asking us how can he use his Surface device
with an eye tracker and software and hardware
in order to use it better to communicate more naturally
with his wife, and to be able to
move his wheelchair independently.
>> That's right.
>> Since that time, the work has evolved.
And so in cooperation with the Windows team,
we created Eye Control for Windows
to allow people to use an eye-tracking interface
to control their Windows device.
>> Yeah, that's just amazing.
I mean, what it has done for anyone with ALS
to be able to, in fact, communicate --
>> Right.
>> --while using Eye Control has been fantastic to see.
>> And so now you're enhancing it in some way?
>> Absolutely, yes.
So, at Build this year, we announced our
Eye Control APIs,
which allow any developer to harness the power
of Eye Control for their own applications
to add accessibility for eye tracking.
>> That's very cool
So, they can start building apps that enhance --
-- or just incorporate Eye Control in the app?
>> Yes. And so one example of that is Eye Drive.
So, it's an open-source initiative that we created
to allow you to do basically a virtual joystick with your eyes.
So you can control things like an RC car
or even a wheelchair.
>> Oh, wow. Do you want to show us that?
>> Absolutely.
>> Okay.
>> So in this research prototype we used an eye tracker
connected to a Surface device.
>> Got it. So, basically, now you're just gazing
where you want to go.
And so this app is just basically a Surface with this app
is what's moving the wheelchair?
>> That's correct. Yep.
I just look where I want to go and it sees where my eyes --
>> And so how do you go back?
Oh, yeah, I see it. You're gazing in the direction --
>> I just look down. Yeah.
So, it's basically just like a virtual joystick.
>> Yeah. That's very, very cool.
So, a developer can just write this
using the Eye Control APIs?
>> Absolutely. Yeah. It's very straightforward.
>> And this remote-control car, same thing?
>> We worked with Team Gleason in order to
create an eye-controlled RC car.
And the basic idea is just how do you have fun
with your loved ones, even though you can
only use your eyes to control your world around you?
We also worked with an individual who was
a former musician, and we made it so he could control
a drum kit with his eyes.
>> Wow.
>> I think we're only just tapping the potential
for what can be done.
Obviously, accessibility is a good entry point,
but I think there's a lot of universal applications as well.
>> That's right. I mean, that's kind of one of the things that
I think developers can really start thinking about, which is
the universal design and these capabilities not only, in fact,
bring more people to participate in
our society and our economy,
>> Right.
>> but it also can enhance the experiences for everyone.
So, where do people go to get started?
>> Yes. So, for more information on
Eye Control for Windows
as well as the Eye Control APIs, you can go to
aka.ms/eyecontrolapi.
>> Thank you so much, Jon.
>> Thank you.
>> It's such a pleasure.
-------------------------------------------
Hunting Out of Pop Ups - Duration: 28:18.
(wind blowing)
(dramatic music)
(upbeat music)
- [Announcer] Yamaha presents the Whitetail Diaries.
Chronicling hunting adventures
of the most plentiful and intelligent big game animal
in North America.
Join top whitetail hunters nationwide,
embark on the amazing adventure that is
hunting the whitetail deer.
(dramatic music)
Now, when hunting, sometimes you can't always
find a place to hang a stand,
or it's not feasible to create a permanent box style blind.
In those cases where you've got to be mobile
and adapt to the current hunting situation,
choosing one of the myriad of portable pop up blinds
will pay off.
These fabric blinds come in all shapes and sizes,
and offer a plethora of features that allow hunters
the ability to quickly set up in a variety of locations.
And be able to hunt a wide range of locations,
while being concealed.
We'll share our feelings, experiences and strategies,
while we also showcase a few hunts from pop up blinds
in today's episode.
- You know, pop up blinds, as I like to call 'em,
they're basically a portable blind that comes out of a box
and you can set 'em up in a lot of different situations,
a lot of different places,
whether it's just for a one day hunt,
or you're setting it up to last for the season.
A few things that I always like to keep in mind
is obviously the construction of the blind,
if I plan on leaving it out for a long time,
and making sure that I get it anchored down,
both tying it off, and driving stakes in the ground
if it's gonna be there a while.
But if it's just something that I'm gonna go out and hunt
for you know, a day or two,
you can just pretty much just pop 'em up and sit down
and you may get lucky right away.
- You know, I love hunting in pop ups,
and the cool thing about pop ups
is you literally can put 'em anywhere.
What I love is is I love kind of scheming
of where deer are gonna come from,
so if I think they're gonna come from a certain area,
and you know deer are gonna do different things every time,
but you kinda have and idea of which way
you think they're gonna come from.
Usually you're either setting up a pop up on a trail,
a place where deer are gonna be traveling
from a bedding area to a feeding area or at a feeding area.
And so, one of the two is usually the best way to go.
The feeding area can be a food plot,
it can be an area that you're actually feeding deer at.
It can be an area that there's green stuff,
it can be a lot of acorns, it can be just about anything.
Wherever you can find deer spending a lot of time,
that's where you'd stick a pop up.
And so, you gotta think about your wind.
When you're thinking about your wind, you know,
a pop up actually will hold a lot of your scent in there.
But still, there's gonna be a little bit of it leak out,
so you would prefer that your wind
be blowing straight in your face.
- [Wade] I mean, I don't know how many deer hunts we've done
out of pop ups over the last, I don't know, 20 years,
but it would be a lot.
You know, pop ups allow you that flexibility
to set up on a deer real quick.
It allows you great ability to hide cameramen as well.
It allows you the ability to get drawn in position,
sometimes you may not be able to for a bow hunter.
It will give you cover
from inclement weather at times even out there,
and finally, it allows you to set up in places
where tree stands and tripods just simply will not work.
- [Narrator] We'll start off this episode
with Michael Wersig, Clark's son in law,
as we follow him on his first handgun hunt
for a special buck.
- My first hunt of the year.
We're going after a velvet buck.
It's gonna be my first handgun ever.
Went down to the range, practiced a lot.
I feel like we're on pretty good.
We're gonna take the Viking six out there,
and hopefully we can make it happen.
So we had this one particular buck,
kinda on the edge of where these two draws come together.
We set up a pop up in the area, and I mean,
they just kinda worked this area early in the morning.
So, we decided to go ahead and trifle.
You know, I'm hunting with a Smith and Wesson
Performance Center .460, and yeah,
I've never hunted with a handgun before.
So that involved me going down to the range,
and I mean, I spent a couple hours down there
just shooting, just trying to get comfortable
with what I was gonna hunt with.
And I mean, what I had to do is,
I mean, I really had to kinda go back to the roots
of open sights hunting.
I mean, now a days, you don't really think about it,
but it takes practice.
I mean, it's like shooting your bow,
you've gotta get everything lined up,
you almost, you have to have kinda anchor points,
and I mean, you just gotta do everything the same.
And the only way to get good at anything is just practice.
And that's just the only way to build confidence
in any weapon you're gonna use.
So we're hunting with Hi Viz fiber optic sights,
and the cool thing about this sight
is the front sight has tritium in it.
And what that does, is I mean,
in low light, it'll give you,
I mean it almost looks like a glow stick
whenever you're hunting.
But then, in the day time, you can still see
or it's not too bright to blind you.
I mean, it's the best of both worlds
is really what it is.
I mean, it's just pretty cool sitting in the stand.
You know you can shoot early, or you can shoot late,
and you're covered.
(gentle music)
So the first morning we get in there,
and I mean, you know, it's early,
and we got deer covering us up.
I mean, they are everywhere,
and we did end up seeing the shooter the first morning
but he kinda stayed behind this thick little bunch of trees
and you know, camera guy couldn't see him,
I couldn't get a shot.
It just never really worked out.
He was a little bit nervous, and you know,
sometimes, that's just the way it goes.
I mean, from beginning of the first morning
to the end of it, I mean, we saw our deer.
I was an exciting hunt, I mean you got to get excited
that you see your shooter.
I mean, how can you not have fun with that?
I mean, you get to come out the next day
and try to get your shooter, so I mean, overall,
I just love sitting in the blind and watching deer.
- [Narrator] When we return,
Michael continues his hunt for his velvet buck.
(dramatic music)
And later in the show, Wade hunts out of a pop up
as well as with a TenPoint Nitro X crossbow.
Ah, stay tuned.
The Yamaha Whitetail Diaries is brought to you by
Yamaha's proven off road ATVs and side by side vehicles,
Bass Pro Shops and Cabela's, your adventure starts here,
Garmin Xero, leave the guesswork behind.
Welcome back to the Yamaha Whitetail Diaries
with Wade Middleton.
We saw Michael begin his first handgun hunt,
but his deer never gave him a shot,
and with this buck being active in the mornings, well,
Michael sets out for another morning hunt.
- We're going out this morning.
It's an early season hunt.
We've got a couple deer still in velvet.
We've got one particular deer we're going after,
and to top it off, I'm hunting with a handgun.
I've never done that before,
and I am real excited to go out there.
I mean, I've always wanted a velvet deer,
had one chance in the past, it didn't work out.
So I got a second chance.
We're going with the Performance Center .460.
It's gonna be an awesome hunt.
So the area that we were hunting in, it's this,
it's this ridge between two draws,
and I mean, it's just flat out pretty.
I mean, you're there and there's a little road
coming down the side of it, and the sun comes right over it,
and I mean, it's just gorgeous.
I mean, you couldn't ask for a better place to hunt.
We're hunting out of a Cabela's pop up,
and I mean, when you're open sights hunting with a handgun,
I mean, you want those deer within 20, 25 yards,
and a pop up is almost always an easy way to set it up.
So I see the deer cross the road.
He's the shooter, I know he's the shooter we want.
And he gets behind these trees,
and he just kinda camps out back there for a little bit.
I guess he's just eating some of those acorns
off those post oaks,
and finally he kinda works his way through this gap,
and he comes out, and he's broadside.
I've got my Walkers on to protect my ears,
I've got my Wiley Xs on for eye protection,
and it just, it takes a little bit of movement
to get everything situated,
you know, get your rest moved, throw the handgun up there,
and pull off a good shot.
Are you good?
(dramatic music)
Are you good?
(shot fires)
(heavy breathing)
Oh, my God.
(heavy breathing)
Oh, my.
That is freaking awesome.
First pistol hunt ever,
I mean, that deer comes in about,
I don't know how many times,
he comes in, he comes out, he comes in, he comes out.
Finally, he gives us a shot, and I mean,
he freaking just got smoked.
I mean, he's just dropped like nothing,
like a sack of rocks,
I mean, that is the coolest thing ever.
The cool, I mean, not only is he in velvet,
it's my first handgun buck.
I mean, the open sights,
it took me a little while to get the feel of it,
and I mean, that's cool.
I love anything that's a challenge,
and I mean, I'm pretty much addicted to that.
I'm probably gonna have to do that again pretty soon.
- [Narrator] Hey, congratulations, Michael,
on your first velvet entry
into the Yamaha Whitetail Diaries.
- [Michael] I am so excited, I mean,
this thing, it is awesome.
That was an amazing hunt.
Let's go get the Wolverine, get him packed up,
and go show the guys.
(gentle music)
- [Announcer] Hey, if you want to learn more
about the Performance Center .460 XDR,
visit Smith-Wesson.com/PC.
Well, coming up next,
it's Wade's turn to hunt out of a pop up,
and don't go anywhere.
The Yamaha Whitetail Diaries is brought to you by
Thompson Center, America's master gunmaker,
ConQuest Scents, hunt scents and dog training scents,
Sawyer, we keep you outdoors,
TenPoint Crossbows, perfection lives here.
Welcome back to the Yamaha Whitetail Diaries
with Wade Middleton.
This show is highlighting hunting out of a pop up blind.
We join Wade as he heads out to one right now.
- It's about 68 degrees or so this morning,
a really, really heavy dew on the ground.
Not a lot of wind, you know,
what wind we've got's kinda coming out of the southeast,
maybe two to four miles an hour.
You know, it is definitely moving in closer to the pre-rut.
We're gonna be in some pop ups,
which is kinda the theme and focus of this show.
I'm gonna go hunt, on this particular hunt,
with the TenPoint Nitro X Crossbow.
That crossbow is the smallest, most compact,
fastest, energy driven crossbow I've ever seen in my life.
And I've had the opportunity
to shoot a lot of crossbows over the years.
I love the way that you cock
this particular model that I have.
It's very simple, it's very easy to use,
whether you be in a tree stand or sitting in a ground blind,
and when you pull the trigger,
the accuracy and the energy
that's coming out of this crossbow,
is basically at this point, second to none.
I mean, I've shot hogs with it, I've shot whitetail with it,
and it just delivers an impact, that like I said,
it's unparalleled.
Hopefully what we'll see this morning,
we've got two or three deer
that we've been kinda trying to hunt on and off
all year long at this particular spot.
It's a small pop up, it's gonna be pretty close together,
but it's perfect for the situation,
because it just fits back in the brush nicely.
So we've got about 30, 45 minutes til daylight.
That'll give us plenty of time to get the Wolverine parked,
be able to get down to the stand, let the sun come up,
and regardless if we get a deer or not,
we'll see what happens.
It's your typical morning set,
that if you're in an area that has a lot of deer,
you know, you start to see a few shapes coming through.
These two bucks that were both in my opinion shooters,
one had like these real sweeping up main beams,
the other one was kind of a classical, more traditional rack
as I would call it.
They were kinda milling around from the left,
and just kinda eased through, and got out in front of us,
and were just feeding around, and you know,
it doesn't get any better to start the day.
In this situation, I mean,
I'm waiting to get good shooting light, both from the,
for the scope, but the camera,
and the deer are moving around,
and they're kinda coming from our left and right,
and we've seen a couple young bucks at the time,
and I know this is gonna be a freehand shot
out the left window.
It's in my lap, you know,
as I'm moving to get into position,
I mean, they just took off running.
They got spooked.
They're gone.
Depending on where you hunt,
sometimes deer don't even know why they ran, you know.
Was it, did a bird spook 'em,
did they get a whiff of a crazy scent,
did a sound off in the distance,
did another deer just take off running?
You know, if nobody blows, and they're not really flagging,
there's a good chance if they're on a food source,
those deer are gonna come back.
It was about 35, 45 minutes later, coming from the right,
kind of off a little rocky hill,
the deer just started working through.
And they came in from the right,
and they're just walking the whole time,
they're just kind of milling around, walking along,
and they are kinda heading back down the same trail
that we had seem them early that morning.
And I'm already on point at this point.
I like both of these deer.
The nine point to me was a more mature deer,
so I was kinda more gravitating towards him,
but I was gonna shoot either one of them.
They were both great deer,
and as they kinda got through that tall grass,
I'm already in my mind trying to position myself
in the different holes in the windows to get a shot.
You on him?
(shot fires)
(leaves rustling)
I mean, that went down fast.
We saw those two deer early this morning.
They came in actually from the left.
(heavy breathing)
This time, they came back in from the right,
and they kinda got the same together right there.
Both of 'em were good shooters.
Tough to get a shot.
Took the little freehand shot on the nine point right there.
You know, this thing is so, absolutely fast,
I mean, I know I hit him, I know I hit him
you know, kinda quartering away,
so I felt like the shot was good, but he's so fast,
that I really couldn't tell you much more than that.
I mean, it is so cool
when you can get in these pop up blinds,
you can put 'em in a lot of different situations.
This one's got a mix of ways that you can build your,
put your windows up.
We've got most of 'em closed
and the sun's coming up behind us,
and you know, we had really a perfect situation.
I really thought I was gonna get a shot this morning,
and a little bitty buck came in on the side
that I didn't know was there,
picked me off raising my crossbow.
This time later in the day, as they were coming back,
you know, who knows what direction they were going,
and why, but they came back in the perfect angle,
gave me a shot.
I feel pretty good, think we smoked that one.
(dramatic music)
- [Narrator] When we return, Wade gathers the search party
and start to track Wade's buck.
The Yamaha Whitetail Diaries is brought to you by
Smith and Wesson Performance Center,
performance when it matters most,
Hi Viz Shooting Systems, see what you've been missing,
Purina Quick Draw mineral blocks, a difference you can see.
Welcome back to the Yamaha Whitetail Diaries
with Wade Middleton.
Wade is confident he made a good shot on a solid nine point,
but as he says, you never know
until you get your hands on 'em.
- You know, just like we always do,
'cause we've got the benefit of a camera,
we play the shot back,
and exactly kinda what I thought happened,
I felt like I was back when I took that shot.
The deer actually takes a step right when I pull the trigger
and I probably tugged it a little bit, too,
because he was easing out on me, and you know,
if you get excited, that happens,
but he's quartering away when I take the shot,
I go in back, but that was the angle I was shooting at.
Obviously, I'm trying to be a lot more forward right there,
and go out, but actually,
I think it went through his whole body cavity
at that speed and that much energy
at about 30 yards right there.
Watched him run off, he was hunched up good,
but I'm gonna give him about an hour, hour and a half,
and slide on out of here.
You know, that's just the best advice
that I could give somebody in that situation.
When in doubt, back out and give him a little time.
Like I said, he took a step,
and I think I pulled it a little bit, you know.
Up and down on his body, I hit right where I was aiming,
but I'm back about four inches, maybe five
from where I was trying to get that shot.
And that's the difference in a step,
and a little bit of a tug by me when I pulled the trigger.
That goes to show you, when you're shooting anything,
you know, ethically out there,
you want to do the best thing you possibly can.
If you think about that shot,
guys that are trying to make
these 80 yard shots with crossbows, I mean,
you shot him in the butt.
I'm only 30 yards right here,
you know, that deer gets two steps
versus that distance there,
it's just, you know, your crossbow can do it,
but let's just be smart when we take those shots.
It's kinda tough on me right now,
but we're gonna find that deer.
So when we came back and got everybody,
and we kinda did our little deal,
we got all of our cameras rolling,
and everybody's milling around, nobody's finding any blood,
off goes Clark, you know, he just goes bee bopping along
down the hill, and all the sudden, he's walking around back,
he's already found the deer.
- It's only 50 yards, maybe 80.
- (laughing) It wasn't even any challenge.
- I see a big white belly, I think it might be a deer.
(laughing)
- That's why you bring your helpers.
(laughing)
We really needed 'em a lot this morning.
I just wanted to go get a taco.
(laughing)
- You know, the great thing is Wade, is you hit that deer,
it looked like, I mean, when we looked at the footage,
it looked like it was back, but he was quartered so hard,
it came out, even forward of the front leg.
- Yeah, more or less.
I mean, I was aiming, at the, you know,
at that opposite side shoulder, that's what I like to shoot
if I'm gonna take that shot.
I still feel like I pulled it
a little bit from where I was aiming,
but man, I mean, and he stepped on me.
When you slow motion, - Right.
- and you can really see it,
but that's where I was trying to go.
I would never take that shot
at a deer quartering the other direction towards you,
but when they're quartering away,
they open up a lot of stuff. - They really do.
- I mean, it went through everything.
- Yep.
Quartering away is always kinda what you,
if it's not perfectly broadside, at least a little away,
and you know you're gonna be good.
- Yeah, you got a lot of places to put it in.
- That's right. - I mean, if it wouldn't
have been for that bush,
I'd have seen him rolling right there,
- I think you would. - 'cause I was watching
the whole time, and I said, when, go down, go down, go down.
- No, that's a great deer.
- It is.
Boy, he was pretty this morning when he came out there.
He came in with another deer that,
man, he was such a bigger more mature looking deer.
Had a little bit of dew on his antlers, shining out there.
- Beautiful.
- Came through early, we couldn't get a shot,
we got busted, and then they circled back around,
later on and came right back.
Thanks for the tracking help, Clark.
(laughing)
- I didn't do anything,
but I'm glad I got to be in on the recovery.
That's pretty fun.
- Look, there's a white belly.
I think we got him. - I think we got him.
- [Narrator] Congratulations, Wade,
on another TenPoint Nitro X entry
into the Yamaha Whitetail Diaries.
To learn more about TenPoint's Nitro X,
or any of their crossbow models, head on over to
tenpointcrossbows.com
and be sure to check out your state's DNR
on any crossbow regulations.
Well, that'll do it for us here
on the Yamaha Whitetail Diaries.
We'll see you next time.
(dramatic music)
(boom)
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