February 2018
Beginner to intermediate
258 pages
5h 47m
English
Content preview from R Deep Learning Projects
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Sentiment Analysis with Word Embeddings
In this chapter, we turn to the problem of sentiment analysis. Sentiment analysis is an umbrella term for a number of techniques to figure out how a speaker feels about a certain topic or piece of content.
A vanilla case study of sentiment analysis is polarity. Given a document or text string (for instance, a Tweet, a review, or a comment on a social network), the aim is to determine whether the author feels good, bad, or neutral about the item or topic in question.
At first look, this problem might seem trivial: A lookup table with positive and negative words, and simply counting the word frequencies should do, right? Not so fast. Here are a few examples of why this is tricky:
- Their decadent desserts ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.