A side-by-side comparison of JAX, Tensorflow and Pytorch while developing and training a Variational Autoencoder from scratch
How to expose a deep learning model, built with Tensorflow, as an API using Flask. Learn how to build a web application to serve the model to the users and how to send requests to it with an HTTP client.
How to train your data in multiple GPUs or machines using distributed methods such as mirrored strategy, parameter-server and central storage.
Building a custom training loop in Tensorflow and Python with checkpoints and Tensorboards visualizations
How to optimize the data processing pipeline using batching, prefetching, streaming, caching and iterators
How to develop high performance input pipelines in Tensorflow using the ETL pattern and functional programming
A guide on how to debug machine learning code and how to use logs to catch errors in production (including a set of useful Tensorflow functions to make your debugging life easier)
Explore unit testing in tensorflow code using tf.test(), mocking and patching objects, code coverage and different examples of test cases in machine learning applications
A deep learning python project template, object oriented techniques such as abstraction, inheritance and static methods, type hints and docstrings
How to use recurrent neural networks and LSTM to forecast cryptocurrencies price