April 2022
Beginner to intermediate
200 pages
4h 17m
English
Content preview from Natural Language Processing with Flair
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Chapter 10: Hands-On Exercise – Building a Trading Bot with Flair
In this final chapter, we will go through a hands-on programming exercise where we will leverage a number of Flair's pre-trained models to build a real-world application. We will build a simple trading bot that uses Flair's Named Entity Recognition (NER) and sentiment analysis tools to make trading decisions. The trading strategy consists of taking the current day's news headlines as input and using NER to determine whether the news articles are discussing a company we are interested in. We will then run sentiment analysis that helps us make a call about whether to hold, buy, or sell this company's stock.
In the first section, we will cover the details of our trading strategy ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.