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The official GitHub repository for the Mathematics of Machine Learning book!
| Date | Stars |
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| 2026-07-31 | 400 |
| 2026-08-06 | 403 |
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<h1 align="center"> Mathematics of Machine Learning</h1> <p align="center">This is the code repository for <a href ="https://www.packtpub.com/en-us/product/mathematics-of-machine-learning-9781837027866"> Mathematics of Machine Learning</a>, published by Packt. </p> <h2 align="center"> Master linear algebra, calculus, and probability for machine learning </h2> <p align="center"> Tivadar Danka</p> <p align="center"> <a href="https://packt.link/math" alt="Discord" title="Learn more on the Discord server"><img width="32px" src="https://cliply.co/wp-content/uploads/2021/08/372108630_DISCORD_LOGO_400.gif"/></a>       <!-- <a href="https://packt.link/free-ebook/9781837027873"><img width="32px" alt="Free PDF" title="Free PDF" src="https://cdn-icons-png.flaticon.com/512/4726/4726010.png"/></a> --> <!--       --> <a href="https://packt.link/gbp/9781837027873"><img width="32px" alt="Graphic Bundle" title="Graphic Bundle" src="https://cdn-icons-png.flaticon.com/512/2659/2659360.png"/></a>       <a href="https://www.amazon.com/Mathematics-Machine-Learning-Calculus-Probability/dp/1837027870/"><img width="32px" alt="Amazon" title="Get your copy" src="https://cdn-icons-png.flaticon.com/512/15466/15466027.png"/></a>       </p> <details open> <summary><h2>About the book</summary> <a href="https://www.packtpub.com/en-us/product/mathematics-of-machine-learning-9781837027866"> <img src="https://content.packt.com/B32104/cover_image_small.jpg" alt="" height="256px" align="right"> </a> Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to elevate their technical expertise. With this book, you’ll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts. PhD mathematician turned ML engineer Tivadar Danka—known for his intuitive teaching style that has attracted 100k+ followers—guides you through complex concepts with clarity, providing the structured guidance you need to deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems. Balancing theory with application, this book offers clear explanations of mathematical constructs and their direct relevance to machine learning tasks. Through practical Python examples, you’ll learn to implement and use these ideas in real-world scenarios, such as training machine learning models with gradient descent or working with vectors, matrices, and tensors. By the end of this book, you’ll have gained the confidence to engage with advanced machine learning literature and tailor algorithms to meet specific project requirements. </details> <details open> <summary><h2>Key Learnings</summary> <ul> <li>Understand core concepts of linear algebra, including matrices, eigenvalues, and decompositions</li> <li>Grasp fundamental principles of calculus, including differentiation and integration</li> <li>Explore advanced topics in multivariable calculus for optimization in high dimensions</li> <li>Master essential probability concepts like distributions, Bayes' theorem, and entropy</li> <li>Bring mathematical ideas to life through Python-based implementations</li> </ul> </details> <details open> <summary><h2>Chapters</summary> | Chapters | Colab | Kaggle | Gradient | Studio Lab | | :-------- | :-------- | :------- | :-------- | :-------- | | **Part 1: Linear Algebra** | | | | | | <ul><li>Chapter 1, Vectors and Vector Spaces</li></ul> | <a href="https://colab.research.google.com/github/cosmic-cortex/mathematics-of-machine-learning-book/blob/main/part-01-linear-algebra/01-vectors-and-vector-spaces.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br> | <
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b2166fa1596014c0, llm:Repository described as 'The official GitHub repository for the Mathematics of Machine Learning book' (book materials, Jupyter Notebooks).