Linear Algebra with Python is designed to + provide a comprehensive + refresher on the essential concepts of linear + algebra, tailored for professionals and students in + fields such as statistics, econometrics, + quantitative analysis, and data science. Whether + you're a seasoned expert or someone looking to + solidify your foundational knowledge, this guide + offers an in-depth exploration of critical topics in + linear algebra, enriched with Python-based + computation and visualization.
+ +Throughout this book, we will delve into key concepts + that are pivotal for advanced quantitative skill + sets, including linear combinations, vector spaces, + linear transformations, eigenvalues and + eigenvectors, diagonalization, singular value + decomposition, and more. Each concept is carefully + explained and demonstrated with Python, making + abstract ideas more concrete and applicable to + real-world scenarios.
+ +Ready to get started? Skip ahead to the Table of + Contents. +
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WHAT IT IS ABOUT
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ISSUES?
+If you come across any applets that aren't working as + they should, examples that could use a clearer + explanation, or even just a typo, I'd really + appreciate it if you could let me know. + + Feel free to report any issues to project's GitHub repository + + +
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DESIGN CREDITS
++ The design of this site was inpired by the + fantastic book + Collision + Detection + written by Jeffrey Thompson. + The current version, released in 2024, was built + thanks to the following projects: +
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SUPPORT + THIS PROJECT
+If you like my work, you can support it using the + links below:
+ + + ++ Thank you for your support! ❤️ +
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NAVIGATION
+OK, let's begin! Click the link at the bottom the + page, or the arrows at the top, to + move to the next chapter. The Complex + Analysis link at the top will + take you back to the Table of + Contents.
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