The code is on GitHub and he also links to the generators available in SciPy. We’ve seen SciPy in some Hackaday contest entries before. You can think of it like Matlab for Python.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

James McCaffrey uses cross entropy error via Python to train a neural network model for predicting a species of iris flower.

This video is an overall package to understand L2 Regularization Neural Network and then implement it in Python from scratch. L2 Regularization neural network it a technique to overcome overfitting.

The only thing you need to have installed is Python. Practically speaking this is very useful to share files inside your local network. Implementing this tiny but hugely useful HTTP server is very ...

New modules are simple to add, as new classes and functions. Models are defined in Python code, not separate model configuration files.

Neural network momentum is a simple technique that often improves both training speed and accuracy. Training a neural network is the process of finding values for the weights and biases so that for a ...