Books

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.

Elements of Programming reimagines software as a discipline of logic, structure, and responsibility. Inspired by Euclid, it presents programming through definitions, postulates, and proofs that build a coherent view of computation. From identity and composition to semantics, type systems, and ethics, the book traces how formal reasoning shapes trustworthy systems. It argues that software is not only a technical creation but also a moral one, expressing human intention and consequence. For readers who value precision, clarity, and integrity, this treatise reveals how truth and purpose meet in code.

From curious beginners to seasoned problem solvers, this book offers a journey through captivating shapes and clever challenges. Boost your creativity and logical thinking with every page!

This book reveals the essential mathematics powering AI, data science, and finance, making complex concepts accessible and exciting for every reader. Discover the practical applications of math that are already influencing your daily life.

Demystify the mathematical foundations of machine learning with this concise, hands-on guide. Dive into the essentials of linear algebra, calculus, and statistics, specifically tailored for practical application with Python and NumPy. No more wading through dense textbooks – get the core concepts you need to build intelligent systems, fast.

CircleD explores the journey from 0D to a Spherical Dimension, blending observation, logic, and imagination into a thought-provoking framework.

This book is the resource the author wishes he’d had when he began his own journey into general relativity later in life. It provides a carefully engineered learning path for the committed self learner, designed to illuminate the specific topics needed to finally achieve a deeper understanding.

A powerful new book on Conformal Prediction by bestselling author and machine learning expert Valery Manokhin, bridging theory and real-world machine learning. Discover how to quantify uncertainty with statistical guarantees—across deep learning, time series, forecasting, and more. Preorder now before the price goes up.

A clear, example-driven introduction to first- and second-order differential equations, focusing on real-world applications across physics, biology, ecology, and economics. Ideal for self-learners, undergraduates, and educators seeking a rigorous yet intuitive approach to ODEs, with detailed LaTeX-rendered solutions and visualizations.

Does math seem like a bunch of arbitrary rules? This book is here to explain clearly why most of the rules aren't arbitrary at all. There are good reasons for them! This ebook contains the first two chapters: fractions and pre-algebra.