Back in 2015. Google released TensorFlow, the library that will change the field of Neural Networks and eventually make them mainstream. Not only that it became popular for developing Neural Networks, but it enabled higher-level APIs to run on top of it. One of those APIs is Keras.
Code that accompanies this article can be downloaded here. Sometime in the last few weeks, while I was writing the explanations for the way in which neural networks learn and backpropagation algorithm, I realized how I never tried to implement these algorithms in one of the programming languages. Then it struck me that I've never tried to implement the whole… Continue reading Implementing Simple Neural Network in C#
In the previous article, we covered learning process of ANNs using gradient descent. However, in the last few sentences, I've mentioned that some rocks were left unturned. Specifically, explanation of backpropagation algorithm was skipped. Also, I've mentioned it is a somewhat complicated algorithm and that it deserves the whole separate blog post. So here it… Continue reading Backpropagation Algorithm in Artificial Neural Networks
In the previous blog posts, we covered some very interesting topics regarding Artificial Neural Networks (ANN). The basic structure of Artificial Neural Networks was presented, as well as some of the most commonly used activation functions. Nevertheless, we still haven’t mentioned the most important aspect of the Artificial Neural Networks - learning. The biggest power of these… Continue reading How do Artificial Neural Networks learn?