A Mathematical Introduction to Data Science with Python

A Mathematical Introduction to Data Science with Python brings the language of mathematics and the practice of Python side by side. Rather than treating data science as a black box, it shows how core ideas unfold step by step in code, making the subject easier to follow for readers who want both the reasoning and the implementation.

Mathematics First, Code Second 💻

This companion textbook is built for readers who already have a basic mathematical foundation and want to see how those ideas appear in working Python examples. It is not positioned as a general Python course. Instead, it uses Python as a practical tool for exploring sets, functions, vectors, matrices, calculus, probability, statistics, and the algorithms that rely on them.

From Foundations to Real Data Science Topics

The book moves in a deliberate sequence: introductory Python, symbolic and numerical tools, linear algebra, matrix decomposition, calculus, advanced calculus, principal component analysis, linear regression, neural networks, probability, statistics, maximum likelihood estimation, and applied data modelling. That structure makes it useful for readers who prefer a gradual, concept-led approach rather than isolated code snippets.

What the Book Emphasizes

• Python implementation of mathematical ideas using libraries such as NumPy, SymPy, Pandas, scikit-learn, Matplotlib, and SciPy.
• Worked examples and exercises that connect formulas to executable code.
• Applied algorithms including PCA, SVD, linear regression, neural networks, and maximum likelihood estimation.
• Practical data modelling with a real dataset from scikit-learn.

Who This Ebook Suits

This title will be most useful to students, self-learners, and technically curious readers who want to understand data science from a mathematical angle while also seeing how the ideas are coded in Python. Readers with some programming familiarity will likely move through it most comfortably, though the early chapters provide a gentle Python introduction for newcomers.

A Useful Companion for Serious Study

If you like learning by seeing the formula and the function call together, this is the kind of book that rewards careful reading. It is especially appealing for anyone who wants a clearer bridge between abstract mathematics and the computational methods used in modern data science.