April 2020
Intermediate to advanced
330 pages
7h 44m
English
Content preview from Hands-On Deep Learning with R
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Technical requirements
We will use the Keras (TensorFlow API) library in this chapter.
We will be using the steam200k.csv dataset. This dataset was generated from publicly available Steam data, which is one of the world's most popular gaming hubs. This data contains a list of items (game-title), users (user-id), and two user behaviors (own and value), where value represents the number of hours played for each game. You can find the dataset at: https://www.kaggle.com/tamber/steam-video-games/version/1#steam-200k.csv.
You can find the code files of this chapter on GitHub: https://github.com/PacktPublishing/Hands-on-Deep-Learning-with-R.
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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.