How to use Keras/TensorFlow for Deep Learning with Python? – Mastering Keras/TensorFlow

Keras is one of the most widely used frameworks for deep learning used today. It runs in Python and runs on top of TensorFlow in the 2.x version, and is therefore one of the primary choices for Deep Learning engineers these days.

However, I find that the Keras documentation is slightly… unwelcoming.

With that, I mean that the docs simply (and perhaps agreeably) describe the Keras APIs, thus the functions that can be used within Keras, without a thorough intuitive explanation about why certain things are as they are.

In this Collection, I will be working towards a comprehensive yet complete overview of Keras. I will teach you how it works and how you can create simple and more complex models in Python. Additionally, I will cover extensions to the Keras framework that have been developed by the deep learning community.

This way, you’ll be up to speed with Keras before you know!

If you wish to acquire more information about deep learning first or wish to know what these ‘Collections’ are, you may be interested in these links:

Please note that this is a work in progress. I always have the motto to publish whatever is ready which allows the reader to start learning already. That’s why you may find that many of the blogs noted below haven’t been finished yet. However, please come back every now and then, because I’ll do my best to add new ones as often as I can.

Also feel free to leave any comments below! 🙂

Getting to know Keras

Basic neural networks

Loss functions

Convolutional Neural Networks

Recurrent Neural Networks


Advanced Activation Layers

Normalization & regularization

Data Preprocessing with Keras

Model visualization

Model interpretability: tf-explain

Model evaluation

Keras Callbacks

Keras automation

Edge AI with TensorFlow & model optimization

Distributed training

Other Keras topics