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Mathematics of Machine Learning. Master Linear Algebra, Calculus, and Probability for Machine Learning Tivadar Danka

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Mathematics of Machine Learning. Master Linear Algebra, Calculus, and Probability for Machine Learning Tivadar Danka - okladka książki

Mathematics of Machine Learning. Master Linear Algebra, Calculus, and Probability for Machine Learning Tivadar Danka - okladka książki

Autor:
Tivadar Danka
Serie wydawnicze:
Learn
Ocena:
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.
The book balances theory and application, offering clear explanations of mathematical constructs and their direct relevance to machine learning tasks. Through practical Python examples, you’ll not only learn the mathematics but also how to implement and use these ideas in real-world scenarios, such as optimizing algorithms or solving specific challenges in neural network training.
Whether you aim to deepen your theoretical knowledge or enhance your capacity to solve complex machine learning problems, this book provides the structured guidance you need. By the end of this book, you’ll gain the confidence to engage with advanced machine learning literature and tailor algorithms to meet specific project requirements.

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O autorze książki

Tivadar Danka is a mathematician by training, a machine learning engineer by profession, and an educator by passion. After finishing his PhD in 2016 (about the arcane subject of orthogonal polynomials), he switched career paths and has been working in machine learning ever since. His work includes applying deep learning to cell microscopy images to identify and phenotype cells, creating one of the most popular open source Python packages for active learning, building a full machine learning library from scratch, and collecting about a total of 100k followers on social media, all by posting high-quality educational content.

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