This folder contains some introductory examples on how to use the deep learning frameworks Keras and PyTorch. These are, at least in my personal perception, the two most commonly used deep learning frameworks.
They are written in a tutorial-like style so you can code along and follow my brief explanations. Some basic knowledge in python, linear algebra and machine learning is helpful.
In addition to these two frameworks, I also recommend Apache MXnet with the Gluon API. A collection of tutorials can be found here. The latter is especially useful to me with its time series modeling toolkit GluonTS when it comes to the use of deep learning models for time series forecasting. More on this topic can be found in my repo "RNN-for-Time-Series".
In case there are some problems with rendering the files, copy/paste the adress of the jupyter notebook in this preview tool.