Books

Learn linear algebra by doing itfrom vector to neural networks

Master machine learning algorithms through worked examples and hands-on practice problems. From logistic regression to neural networks, this companion exercise book provides step-by-step solutions and progressive difficulty levels to build deep understanding.

I am a programmer who knows clever tricksI convert integers to bases two to thirty sixBy using character arrays as stringsI can show you amazing math things While others talk about politics and sportsI read about computers of all sortsProgramming languages are all the sameWhen you see arithmetic as a game I don’t write code for a job to be paidBut to understand the video games I playedTo see what works and find out whyTo create, use, study, share, and modify

There’s a certain satisfaction in solving a differential equation by hand.You examine it, try a substitution, watch the terms rearrange

A deep dive into advanced integration techniques used in mathematical olympiads and integration competitions, with clear explanations and fully worked solutions.

Most people think they are bad at math. In reality, they were never taught arithmetic properly.This book is a modern English edition of Arithmetic by Alexander P. Kiselev—the text that formed the backbone of mathematical education in Russia and USSR for over a century and helped produce generations of exceptionally strong mathematicians, scientists, and engineers.Unlike modern textbooks that prioritise shortcuts, visuals, and lowered expectations, Kiselev builds arithmetic logically, systematically, and rigorously. Every method is explained. Every operation has meaning. Exercises are carefully sequenced to develop real understanding—not rote pattern-following.This book does not promise “easy math”. It promises something better: clarity, confidence, and competence.Whether you are a student, a parent, a tutor, or an adult rebuilding fundamentals, this book will change how you understand arithmetic—and why so much later mathematics suddenly becomes easier.

The author explains about a new way to demostrate that the Goldbach's conjecture is correct.

El autor plantea una forma diferente de abordar la prueba de la conjetura fuerte de Goldbach

A rigorously structured, intuition-first calculus guide that takes learners from fundamental ideas to advanced techniques using clear explanations, visual reasoning, and complete logical continuity throughout.

A 20-page PDF summaries of Game Theory essentials, covering Nash Equilibrium, Shapley Values, and Stable Matchings.

This book presents both the fundamentals and advanced topics of finite element analysis and design optimization in a concise and pedagogically structured manner

Mastering Advanced Time Series Forecasting in Python is the definitive sequel to the #1 forecasting bestseller. Designed for practitioners who want to go beyond ARIMA and basic ML, this book takes you deep into probabilistic forecasting, hierarchical coherence, and cutting-edge foundation models—backed by production-ready Python code. Learn how to assess forecastability, build scalable pipelines, quantify uncertainty, and deploy systems that deliver real business impact. Written by a globally recognized expert whose methods power multimillion-dollar decisions, this is the practical, honest, and advanced guide every data scientist, ML engineer, and quantitative professional needs to master modern forecasting.

10 coloring pages✔ Large, clear numbers✔ Fun illustrations for children✔ Printable PDF format✔ Suitable for schools, mothers, and teachers

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from the Software Diagnostics and Observability Institute and the Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, root cause analysis, debugging, crash and hang dump analysis, and software trace and log analysis written from 15 April 2024 to 14 November 2025.