Tensorflow Extended (TFX) in action: build a production ready deep learning pipeline
A tutorial on how to get started with Tensorflow Extended and how to design and execute a Deep Learning pipeline
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
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.
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.
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 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 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
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)
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
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
Predict Bitcoin price with Long sort term memory Networks (LSTM)
How to use recurrent neural networks and LSTM to forecast cryptocurrencies price