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

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

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

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

Deep Learning in Production: Laptop set up and system design

Deep Learning in Production: Laptop set up and system design

An article course on how to write and deploy deep learning systems in production. python code optimization, cloud hosting and system design

Neural Network from scratch-part 2

Neural Network from scratch-part 2

How to buld a Convolutional neural network library using C++ and OpenCL

Neural Network from scratch-part 1

Neural Network from scratch-part 1

How to buld a neural network library using C++ and OpenCL

Document clustering

Document clustering

Use unsupervised learning to cluster documents based on their content