Top /r/MachineLearning Posts, April: New Google Machine Learning Videos, Deep Learning Book, TensorFlow Playground
Check out the most popular topics on Reddit's Machine Learning subreddit from April, including TensorFlow, deep learning, tutorials, self-reflection, and free books.
April on /r/MachineLearning brings top posts in deep learning video tutorials and books, the TensorFlow Playground, deep conversation centered on an xkcd comic from 2014, Microsoft cognitive APIs, and a meta-conversation on the subreddit's direction. Read on for links to, and insight into, the top subreddit stories of the month, along with the number of upvotes of the top posts.
The Google Developer YouTube channel has launched a new video series, titled Machine Learning Recipes. There are 3 videos in the playlist, as of this writing. The series, hosted by Josh Gordon, consists of video topics such as "What Makes a Good Feature?" and "Visualizing a Decision Tree." This link is directly to the first of the videos.
2. TensorFlow Playground +458
Visualize a neural network in your browser, utilizing the underlying TensorFlow architecture. Aside from this, the Google Playground includes this no-nonsense advice:
For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start. For more a more technical overview, try Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
3. Deep Learning Book is Complete +407
This is a link to a Facebook post by Ian Goodfellow, announcing the completion of the deep learning book by Goodfellow, Bengio, and Courville. KDnuggets covered this when it was announced, and our post included additional insight into this announcement, the book, and its contents.
This xkcd comic has the caption, "In CS, it can be hard to explain the difference between the easy and the virtually impossible." The single panel comic illustrates a pair of related requests of a programmer from a muggle: one which would take a few hours, and one which is nearly impossible. The comic was posted with the intent of showing how far machine learning and AI have come over the past pair of years (as some would argue the "impossible" request would now be possible), and an appropriately heated conversation ensues in the subreddit comments.
Recent KDnuggets featured blogger Piotr Migdal asks on /r/MachineLearning whether or not deep learning is the only topic that gets any local love these days, which sparks a conversation on where deep learning and non-deep learning topics fit in on the machine learning subreddit. Self reflective, therapeutic, explanatory, and oh-so-very meta.
Here is a link to a set of cognitive APIs (a seemingly new trend), designed for fast and flexible integration of vision, speech, language, knowledge, and search into developer projects, regardless of platform or language used in implementation.
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