How-to Build a Transformer for Language Classification in TensorFlow

Do the markets reflect rational behavior or human irrationality? Mass psychology's effects may not be the only factor driving the markets, but it’s unquestionably significant.

This fascinating quality is something that we can measure and use to predict market movement with surprising accuracy levels.

With the real-time information available to us on massive social media platforms like Twitter, we have all the data we could ever need to create these predictions.

But then comes the question, how can our computer understand what this unstructured text data means?

That is where sentiment analysis comes in. Sentiment analysis is a particularly interesting branch of Natural Language Processing (NLP), which is used to rate the language used in a body of text.

Through sentiment analysis, we can take thousands of tweets about a company and judge whether they are generally positive or negative (the sentiment) in real-time! We will cover:

> Getting Twitter Developer Access
  - API Setup
> Twitter API
  - Searching for Tweets
  - Improving our Request
> Building Our Dataset
> Sentiment Analysis
  - Flair
  - Analyzing Tesla Tweets
> Historical Performance
  - TSLA Tweets
  - TSLA Ticker