Books

This book describes the algorithms and procedures used to fit statistical models to data. The material covered is taught in the Advanced Statistical Computing course in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.

Greenhouse gas emissions have caused considerable changes in climate, including increased surface air temperatures and rising sea levels. This e-textbook presents a series of laboratory exercises in R that teach the Earth science and statistical concepts needed for assessing climate-related risks. These exercises are intended for upper-level undergraduates, beginning graduate students, and professionals in other areas who wish to gain insight into academic climate risk analysis.

A rigorous treatment of linear models for self learning data scientists. This book is only available in pdf form.

Biological Data Science with R covers data manipulation with dplyr, visualization with ggplot2, essential statistics, survival analysis, RNA-seq analysis, phylogenetic trees, predictive modeling and infectious disease forecasting, text mining and natural language processing, and more.

Zefs Guide to Deep Learning is a short guide to the most important concepts in deep learning, the technique at the center of the current artificial intelligence revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages!

Aprende los conceptos básicos del Machine Learning y avanza poco a poco con teoría y divertidos ejercicios prácticos en Python a niveles intermedios y avanzados hasta llegar al Deep Learning.Tu camino para convertirte en un Científico de Datos comienza aquí

"Mastering SEO: A Complete Guide to Search Engine Optimization for Success" is your ultimate resource for navigating the complexities of SEO. Packed with advanced strategies and practical insights, this book covers everything from on-page and off-page optimization to the latest trends and AI integration. Whether you're a beginner or an experienced digital marketer, you'll learn how to drive traffic, boost rankings, and stay ahead of the competition. Unlock the secrets of SEO success with clear, actionable advice that guarantees results. Don’t just improve your rankings—master the art of SEO!

*3D Printing for Success: Engineering, Innovation, and Income* is your ultimate guide to mastering 3D printing technology and turning it into a profitable business. From understanding the basics to exploring advanced strategies, this book provides actionable insights, expert tips, and real-world examples to help you succeed in the rapidly evolving world of 3D printing. Whether you're starting a new business, optimizing your existing one, or looking for creative ways to monetize your skills, this book offers the tools and knowledge you need to innovate, create, and thrive. Unlock new income opportunities with 3D printing and take your entrepreneurial journey to the next level!

Prologue + Part 1 (PDF version) : In order to put an end to all the religious stuff, Alex - assisted by his girlfriend Nicole - sets out to prove that God doesn't exist with the help of a questionnaire... and boy, is he going to screw things up!

Are all problems worth solving? The following white paper is going to challenge you to answer that question for yourself. In order to do this you'll follow the ADDIE process combined with cognitive Learning Outcomes. Understanding this method will allow you to flip your perspective and measure cognitive development more effectively.

This book teaches you to design, analyze, and draw meaningful conclusions from experiments and observational studies.  Experiments such as A/B testing and observational data obtained by scraping the web, are commonly encountered in data science.  Many examples are also included from the sciences and social sciences.

This book introduces the topic of Developing Data Products in R. A data product is the ideal output of a Data Science experiment. This book is based on the Coursera Class "Developing Data Products" as part of the Data Science Specialization. Particular emphasis is paid to developing Shiny apps and interactive graphics.

Move beyond the API. Dismantle the AI black box and build generative engines from scratch with pure Python and NumPy. Master the profound geometric principles and applied mathematics driving LLMs and Transformers. Transform from a mere consumer into an elite AI innovator by writing the core mathematical architecture yourself—no shortcuts, no frameworks, just pure engineering excellence.

AIエージェントの構築が、これほど容易だった時代はない。そして、実際に機能するものを作ることが、これほど難しい時代もない。本書は言語モデルの基礎から本番対応マルチエージェントシステムまで、失敗が起こる前に予測し、壊滅的な障害ではなく優雅な劣化を設計し、完全なアーキテクチャの所有権を確立するための深さをもって、あなたを導く。ペーパーバック版はamazonにて好評発売中。