Learn Tensorflow and Keras for building Deep Learning applications

Software · Tensorflow · Pytorch · Autoencoders

JAX vs Tensorflow vs Pytorch: Building a Variational Autoencoder (VAE)

A side-by-side comparison of JAX, Tensorflow and Pytorch while developing and training a Variational Autoencoder from scratch

MLOps · Software · Tensorflow

Deploy a Deep Learning model as a web application using Flask and Tensorflow

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.

MLOps · Software · Tensorflow

Distributed Deep Learning training: Model and Data Parallelism in Tensorflow

How to train your data in multiple GPUs or machines using distributed methods such as mirrored strategy, parameter-server and central storage.

Software · Tensorflow

How to build a custom production-ready Deep Learning Training loop in Tensorflow from scratch

Building a custom training loop in Tensorflow and Python with checkpoints and Tensorboards visualizations

Data Processing · Software · Tensorflow

Data preprocessing for deep learning: Tips and tricks to optimize your data pipeline using Tensorflow

How to optimize the data processing pipeline using batching, prefetching, streaming, caching and iterators

Data Processing · Software · Tensorflow

Data preprocessing for deep learning: How to build an efficient big data pipeline

How to develop high performance input pipelines in Tensorflow using the ETL pattern and functional programming

Software · Tensorflow

Logging and Debugging in Machine Learning - How to use Python debugger and the logging module to find errors in your AI application

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)

Software · Tensorflow

How to Unit Test Deep Learning: Tests in TensorFlow, mocking and test coverage

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

Software · Tensorflow

Best practices to write Deep Learning code: Project structure, OOP, Type checking and documentation

A deep learning python project template, object oriented techniques such as abstraction, inheritance and static methods, type hints and docstrings

Recurrent Neural Networks · Tensorflow

Predict Bitcoin price with Long sort term memory Networks (LSTM)

How to use recurrent neural networks and LSTM to forecast cryptocurrencies price