Books Math for Data Science Book by Omar Hijab

"Math for Data Science" by Omar Hijab is a comprehensive textbook that presents the essential mathematical foundations necessary for studying and working in data science. The book covers key areas including linear algebra, calculus, probability, and statistics, tailored specifically for their applications in data science tasks such as principal component analysis and neural network training.

It highlights the importance of these mathematical concepts in understanding and developing machine learning models, with a particular focus on how methods like stochastic gradient descent optimize neural networks. Python code examples, Jupyter notebooks, and exercises support practical learning and application.

Suitable for both students and professionals, this book aims to bridge the gap between theoretical math and practical data science problems, offering a self-contained, logical development of concepts from real numbers and functions through advanced topics relevant to modern AI and machine learning workflows.

Additionally, the book includes numerous exercises (hundreds) with solutions to help readers solidify their understanding.