Course: Deep Learning A-Z™: Hands-On Artificial Neural Networks

Instructor: Kirill Eremenko and Hadelin de Ponteves

Status: Completed

About:

As a long time self taught learner, I have completed courses on different aspects in the data revolution we are witness. From visualizations in Tableau to analysis in Python, I found this course challenging, especially towards the end.

I enjoyed the intuition on many complex deep learning concepts. However, I would have liked the projects to have been more practical.

These are my notes. Hence, you might found my notes to be not useful for you, which is ok. You should use my notes are a reference. Since this was my first Deep Learning course thus, a lot of my notes are basic and even redundant.

As a Python aficionado, I was highly pleased that the code implemented many staple libraries in Python such as Keras and PyTorch.

1. Artificial Neural Networks
2. Convolutional Neural Networks
3. Recurrent Neural Networks
4. Self-Organizing Maps
5. Boltzmann Machines
6. Auto Encoders