Learn Deep Learning with NumPy on Artintellica

Today, I’m thrilled to announce the launch of the Learn Deep Learning with NumPy course on Artintellica. This new course is fully open source and covers simple neural networks and multilayer neural networks using NumPy, starting with the basics, such as elementary vector and matrix operations.

The course uses NumPy, which provides basic linear algebra operations but does not include any advanced machine learning features. As a result, the student must implement everything from scratch. This is a great way to learn deep learning. The course involves updating a neural_network.py file to include neural network features such as gradient descent, backpropagation, and more.

The course was written using my Neovim plugin called ChatVim, which is essentially a way to chat with Markdown files in Neovim. Using models from both xAI and OpenAI, I produced what is, in essence, an entire textbook on deep learning, including exercises. To learn deep learning, simply solve the exercises in the textbook.

I have already started working on the next course on reinforcement learning. Follow along here: Learning Reinforcement Learning with PyTorch.