Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and ...

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...

This is a concise Python 3 programming tutorial for people who think that reading is boring. I try to show everything with simple code examples; there are no long and complicated explanations with ...

Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive ...

Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and modify the code in your browser. What ...

Abstract: I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 23 papers covering different aspects of communication networks. In particular, ...

Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were done in Google Colab. Therefore, you should check the ...

“The only way to learn a new programming language is by writing programs in it.” ...

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If you have any confusion about the code or want to report a bug, please open an issue instead of emailing me directly, and unfortunately I do not have exercise answers for the book.