Hi and welcome to this email, because so now we are ready to start coding and to start building a car
using boats, and as I said before, what we will do now for the first two applications is to use personal
MLP model, which in this case will be a CNN four classification.
And we will try to improve it using the different tools that we can have with birds.
And the first thing will be to use the Conesa that they use in birds.
And the second one will be to use birds as an invading layer.
And we will see how little by little we can improve the accuracy on the test set with that.
So, as I said, we will go into a classification task and more precisely, we will try to build a sentimental
analyzer.
So it's a tool that, for a given text input will give us the feeling that it conveys or more precisely,
it will just give us a plus one if it thinks that the feeling is positive and zero if it thinks that
the feeling is negative.
So, yeah, the idea is to assess whether a text is positive or negative in terms of feeling.
So the data that we will be using comes from Stanford actually, and it's a bunch of hundreds of thousands
of tweets that have been automatically downloaded and they have been automatically labeled to using
the Smileys on the tweets.
So one may argue that it's not really accurate and it could be some tricky concepts like Arani or things
like that.
But we will say that it's more than enough and it is actually just to assess how our performance.
So of course, we need to get this data.
And to do that, all you have to do is in your favorite Web search engine to search for sentiment,
140 academics and you need to go to these websites.
So it helps that sentiment, 140 that counts for students.
And if you think that you arrive in these websites and you can download the data on this Stanford link
right here, so you will get to files one which is trained at sea as V and the other one test that CSB
and the idea is to put them right here in your personal Google Drive folder, because the best way in
Google Cloud to have access to personal files is to put them in a personal Google Drive folder.
And then I will show you later how to access them.
By the way, we downloaded the two files, but we will actually only use the train, the train sets,
and we will by ourselves be able to test it out of it.
The reason is that I don't really know why, but in the test sets, there are three different labels
possible.
So I guess there is also kind of a neutral sentiment for the tweets, but it doesn't appear in the training
set.
So that would be quite weird to train on only two labels, but to try to test it with three labels.
So that doesn't really make sense.
So that's why we will only work with the train that see as we fight.
So that's it.
Just download files with this 10 for link.
Once you have it, drag and drop it in your personal Google folder.
And I guess now we are ready to start coding our AI.
So let's get into it right now and see soon.