The run and pause button is used to start running the epochs continuously until you decide to stop it. While the epochs are running, the model will keep training. There is a reset button to reset the entire network on the left side of the Play button. The right side of the play button is the step increase button used to increase the epochs by one step at a time. This button is useful because the run/pause button sometimes might be too fast to reach the appropriate result.

The recent successes of deep learning have led to a wave of interest from non-experts. Gaining an understanding of this technology, however, is difficult. While the theory is important, it is also helpful for novices to develop an intuitive feel for the effect of different hyperparameters and structural variations. We describe TensorFlow Playground, an interactive, open sourced visualization that allows users to experiment via direct manipulation rather than coding, enabling them to quickly build an intuition about neural nets.

You may have heard the buzz about neural networks and deep learning, and want to learn more. But when you learn about the technology from a textbook, many people find themselves overwhelmed by mathematical models and formulas.

This is how simple neurons get smarter and perform so well for certain problems such as image recognition and playing Go. Inception: an image recognition model published by Google (From: Going deeper with convolutions, Christian Szegedy et al.) Some published examples of visualization by deep networks show how they're trained to build the hierarchy of recognized patterns, from simple edges and blobs to object parts and classes. In this article, we looked at some TensorFlow Playground demos and how they explain the mechanism and power of neural networks. As you've seen, the basics of the technology are pretty simple.

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. 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.

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. 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.