Youtube daily May 31 2017

- One use case is

to use BigQuery for Preprocessing

of the training data.

So the TensorFlow or the Machine Learning Engine

or ML Engine itself is not suited

for the duty of preprocessing

or collecting all the data from Enterprise Systems.

So you can use BigQuery as a data bank

so you can gather all the data

coming from the Enterprise

application server, with server databases.

All imported to the BigQuery and do some preprocessing on that,

then you can add exported data, other training data

to the TensorFlow or ML Engine.

So let's take a look at the actual demonstrations for that.

Here, I'd like to use the Cloud Datalab

to do--to use the BigQuery for preparation,

or preprocessing and use the TensorFlow

to train your Neural Network model

for machine learning analytics.

So this is just something I have prepared

that is called Classifying Manhattan.

Here we are importing the bunch of the location data

from BigQuery and trained the Neural Network model

to classify whether each location is Manhattan or not.

So...

We clear all the cells first.

And now let's take a look at what kind of the training datas

that we'll be using by executing this query.

So I'll be using the--

another public data set called NYPD Collisions.

That because all of the car accidents

happened in the New York City.

We see timestamp and borough and latitude and longitude.

But you cannot use this raw data as it is.

You have to do preprocessing to that.

Because you can see that some rows

doesn't have any borough data.

Some rows doesn't have latitude and longitude.

We have to remove

useless garbage data.

So again, you can use the BigQuery

to do this kind of the preprocessing.

And also, I want to have a new program.

Is Manhattan -- to have a flag.

That flag represents whether the latitude and longitude

is inside Manhattan or not.

So this is the SQL I'll be using for preprocessing

and let me execute it.

And also, you can also execute another

called to extract all the data from BigQuery,

import it into the Python.

So now you have all the data imported into Python code.

So as you can see, by using Cloud Datalab,

you can seamlessly integrate the BigQuery query

with the Python code you write.

And you can continue use your scikit-learn

or the NumPy code running on BigQuery.

Sorry about my voice.

So now we have the training data set.

One is Manhattan.

This could be used as a label for training,

whether each location is in Manhattan or not,

and pairs of the latitude and longitude.

10,000 rows.

So let's do the feature scaling.

Before starting training, usually in machine learning,

you have to clean the data out.

Clean out--cleansing of the data.

And one important thing there is to do is feature scaling.

And if you do the scaling and plotting the data,

you can see the training data set would look like this.

Now everything is centered on...

The, uh...zero.

But still, you can see the shape of Manhattan here.

You can still--

You can even see there's Central Park inside the data set.

So this will be the training data set for neural network.

We'll be splitting the data into training data

and test data.

And use TensorFlow to define your neural network.

Here I'm using TensorFlow, especially the so-called high--

what is that? High-level API of TensorFlow.

And this is one of the features we have recently announced

with TensorFlow 1.0

where you can just write a few lines of Python code

to define neural networks.

Before that, we had been using so-called low-level API

where you have to define all the competition graph--

low-level competition graph to define your own neural networks.

But now you can just write a few lines of code with Python.

So you can see we are defining deep neural networks

with the four hidden layers

and each hidden layer has 20 nodes.

We have the neural networks.

Let's check the current accuracy

of the neural networks and how these neural networks

can classify Manhattan with that,

before doing the actual training.

So now you'll be seeing the map

classed by the neural networks.

So this is how a neural network thinks

where the Manhattan is before training.

So because this is before training,

the neural network is stupid enough--

is too stupid to classify Manhattan.

He thinks this is Manhattan.

So this is where we have to train the neural network model.

The accuracy is 75%.

So you can write a full loop

to repeatedly call the fit method

to train the model by using the training data set.

So now it should be showing the--

gradually showing the better accuracy.

So you are seeing that neural network model is trying

to adjust how to classify each data points

to get better result.

So that network is getting much smarter and smarter

as you have saw on the Playground demonstration.

Yes, it's getting much, much better.

So now training is finish.

We got the 99.8% accuracy.

And now neural network is trying to split the Manhattan

and Brooklyn with the very sophisticated code between them

For more infomation >> Classifying Manhattan with TensorFlow - Duration: 6:18.

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Mera in Aquaman 2018, Gotham City Sirens Movie, Joss Whedon's Batgirl - Beyond The Trailer - Duration: 9:35.

While it all started with Black Widow

who truly came into her own

with 2012's The Avengers

five years later

- poor Scarlett Johansson -

it looks like it will be Wonder Woman

who finally proves to the suits in Hollywood

that female superheroes are worth the investment.

For more infomation >> Mera in Aquaman 2018, Gotham City Sirens Movie, Joss Whedon's Batgirl - Beyond The Trailer - Duration: 9:35.

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Cracked heels home remedy - Cracked heels treatment - Duration: 3:13.

cracked heels treatment at home

cracked feet also known as heel fissures are a common problem for people of all

ages caused mainly by lack of moisture other causes include staying for long

hours using hard soaps cold weather continuous exposure to water overweight

and wearing inappropriate Footwear conditions such as eczema psoriasis

thyroid disease and diabetes can also contribute to this problem

scrubbing

before going to bed mix some liquid soap in a bathtub filled with warm water soak

your feet in this warm soapy water for about 20 minutes use a pumice stone to

gently exfoliate dead skin cells loosened rinsed feet with clean water

and dry with a soft towel apply some foot cream or moisturizer and wear a

pair of clean cotton socks overnight follow this remedy daily until your

cracked feet heal completely

coconut oil

before going to sleep soak your feet in warm water and rub with a sponge dry the

feet well and apply coconut oil generously on the feet put on a pair of

clean cotton socks at night the next morning remove the socks and wash your

feet do this daily for several days until you are satisfied with the results

you can also use olive oil in the same way

mentholated rub

apply a little menthol rub on clean dry feet before bedtime put on a pair of

socks and leave it on overnight the next morning remove your socks and wash your

feet with warm water repeat daily for a few days until rough skin peels off

paraffin wax

heat a little paraffin wax in a microwave or double boiler and add an

equal amount of mustard oil or coconut oil to it apply this thick creamy paste

to the cracks and put on a pair of socks leave it overnight and wash your feet

thoroughly in the morning follow this remedy daily for one to two weeks

glycerine

make a mixture of equal parts of glycerin and lemon juice you can also

add some rose water apply it on your feet leave on for 20 minutes and wash

with water follow this remedy daily for two weeks

you

For more infomation >> Cracked heels home remedy - Cracked heels treatment - Duration: 3:13.

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Lucius Believes Hugo Strange Has An Antidote For The Virus | Season 3 Ep. 21 | GOTHAM - Duration: 1:41.

- An antidote?

Lucius, I could kiss your face.

Before you do that, I don't actually have the formula.

But there is an antidote, that's what you're saying?

I was going through the papers you recovered

from the Owl leader's house.

They suggest that while Strange was working to weaponize

the Tetch virus, he was also working on a parallel project

tailoring different anti-viral agents to his own ends.

Strange was designing an antidote.

That makes sense.

The Court was careful to protect its own.

They would want to safeguard.

We need to talk to Strange.

Is he still here or has he been moved?

Uh, well, when you were buried in the coffin

and the city was about to be virus bombed,

some decisions had to be made.

Harvey.

I told Alfred to question Strange.

In exchange for him telling us where

the bombing was going to go down, Alfred let Strange walk.

Yes, I'm blaming it on the butler.

[dramatic music]

Strange is weasel.

He tried to get as far away from this as possible.

Union Station is shut down.

Downtown train station's our best bet.

Wait up.

Harvey.

Lucius, I know what you're going to say, all right?

He can handle this.

Hell, Barnes had the virus for weeks before anyone knew.

But I was going to say, from all

I see here, Strange's virus is an accelerated

version of the Tetch virus.

Why do you think people are reacting so quickly?

Gordon isn't going to be able to fight this for long.

Well, we'll just have to wait and see, huh?

You keep working on that antidote.

For more infomation >> Lucius Believes Hugo Strange Has An Antidote For The Virus | Season 3 Ep. 21 | GOTHAM - Duration: 1:41.

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WoW Legion PvP Gameplay Patch 7.2 - Arms warrior Bladestorming in Tarren Mill vs South Shore - Duration: 14:01.

WoW Legion PvP Gameplay Patch 7.2 - Arms warrior Bladestorming in Tarren Mill vs South Shore