The amazing website http://playground.tensorflow.org can help you open a Neural Network on your Web Browser. The GUI is mind blowing, and you could download all the codes to study or to build your own project.

Now, The Good News! Amro and Ray Phan have created the MATLAB version of the NN playground, it looks just like the GUI of the Tensorflow version. However, it is not tensorflow-based, it is built on the Neural Networks Toolbox of Matlab (>R2009b). The authors said they are inspired by the [TensorFlow Neural Networks Playground] interface readily available online, so they created a MATLAB implementation of the same Neural Network interface for using Artificial Neural Networks for regression and classification of highly nonlinear data.

Here is the snapshot of the program on my desktop, it looks amazing! Most importantly, it is open source, Matlab lovers could learn a lot from the codes and create new apps.

Briefly speaking, there are two files that accompany this repo:

NeuralNetApp.m: The GUI that creates the interface as seen on TensorFlow Neural Networks Playground but is done completely with MATLAB GUI elements and widgets.

NeuralNet2.m: The class that performs the Neural Network training via Stochastic Gradient Descent. This is used by the “NeuralNetApp.m” app.

Moreover, there is a small demo to show you how to use this class, here is what I got by running the “deom_nn.m“, the simple XOR problem.

For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start. For a more technical overview, try Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville; also please take a look at Andrej Karpathy’s convnet.js demo and Chris Olah’s articles about neural networks.

Data Scientist and Machine Learning Technologist: Translating modern machine learning and computer vision techniques into engineering and bringing ideas to life to built a better future.
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