Books
Satellites capture massive volumes of imagery every day, but turning pixels into insight requires AI. This book teaches you to build, train, and apply deep learning models to real satellite imagery using Python and open-source tools, with 23 chapters of executable code you can run today. All code examples are freely availabe at https://book.opengeoai.org.
- My Adventures with Large Language ModelsBuild foundational LLMs from Transformers to DeepSeek, from scratch, in PyTorch.Prathamesh S.
Build GPT-2, Llama 3, and DeepSeek from scratch in PyTorch. Every chapter has runnable end-to-end code and loads real pretrained weights. Goes well past where most LLM tutorials stop.
Skip the black-box frameworks. Build a production-grade AI coding agent from scratch in pure Python - cloud or local, tested with pytest, all in a single file.
- GeoAI con PythonUna guía práctica de inteligencia artificial geoespacial de código abiertoQiusheng Wu
Los satélites capturan enormes volúmenes de imágenes cada día, pero convertir píxeles en conocimiento requiere IA. Este libro te enseña a construir, entrenar y aplicar modelos de aprendizaje profundo a imágenes satelitales reales utilizando Python y herramientas de código abierto, con 23 capítulos de código ejecutable que puedes probar hoy mismo. Todos los ejemplos de código están disponibles gratuitamente en https://book.opengeoai.org.
Unlock the power of geospatial data with Python! This hands-on guide is designed for beginners and intermediate users eager to explore spatial analysis and interactive mapping using open-source tools. You'll learn how to work with real-world data through practical examples and build skills in Python programming, vector and raster analysis, web mapping, and cloud computing. Whether you're a student, researcher, GIS professional, or data scientist, this book will equip you with the tools to tackle geospatial challenges with confidence. Color-print copies are available through Amazon.
- Interpreting Machine Learning Models With SHAPA Guide With Python Examples And Theory On Shapley ValuesChristoph Molnar
Master machine learning interpretability with this comprehensive guide to SHAP – your tool to communicating model insights and building trust in all your machine learning applications.
- Introduction to Japanese Natural Language ProcessingMasato Hagiwara and Paul O'Leary McCann
A thorough guide for programmers working with Japanese text, covering fundamental issues like tokenization and recent research topics like generating natural language texts. Working examples are accompanied by extensive reference to allow problem solving even without a background in Japanese or Machine Learning.
- Creating AI Agents with MCP - Model Context ProtocolPart of the series, "The Only Book You'll Need On..."Lydia Evelyn and Bruce Hopkins
Get started quickly, creating applications for the Model Context Protocol (MCP) using the official MCP SDKs for Python, Java 21, and Node.js. Quickly master, all of the concepts needed in order to build MCP servers, including transport protocols, tools, resources, prompts, roots, and sampling. Learn how to get familiar with popular MCP client applications such as, Claude Desktop, Postman, and the MCP Inspector.
- Creating TUI Applications with Textual and PythonMichael Driscoll
Learn how to create amazing lightweight user interfaces using Python and Textual in your terminal! You will learn the basics of Textual and then create ten different applications.
- Discrete Mathematics for Computer ScienceAlexander S. Kulikov, Alexander Golovnev, Alexander Shen, Vladimir Podolskii, and Marie Brodsky
This book supplements the DM for CS Specialization at Coursera and contains many interactive puzzles, autograded quizzes, and code snippets. They are intended to help you to discover important ideas in discrete mathematics on your own. By purchasing the book, you will get all updates of the book free of charge when they are released.
Satélites capturam enormes volumes de imagens todos os dias, mas transformar pixels em conhecimento requer IA. Este livro ensina você a construir, treinar e aplicar modelos de aprendizado profundo a imagens de satélite reais usando Python e ferramentas de código aberto, com 23 capítulos de código executável que você pode usar hoje mesmo. Todos os exemplos de código estão disponíveis gratuitamente em https://book.opengeoai.org.
- Gestión de Datos Espaciales con DuckDBDesde los Fundamentos de SQL hasta el Análisis Geoespacial AvanzadoQiusheng Wu
Desbloquea el poder de DuckDB para la analítica geoespacial moderna. Esta guía práctica ayuda a los profesionales de SIG a dominar la gestión eficiente de datos espaciales, transformando grandes conjuntos de datos del mundo real en conocimientos valiosos mediante SQL, Python y la extensión espacial de DuckDB. La edición impresa a todo color está disponible en Amazon.
- Python LoggingMichael Driscoll
Logging is great for debugging and auditing. You'll learn how to log properly with Python in this book!
- Introduction To Conformal Prediction With PythonA Short Guide For Quantifying Uncertainty Of Machine Learning ModelsChristoph Molnar
This book teaches you how to quantify the uncertainty of machine learning models with conformal prediction in Python.
- QuantLib Python CookbookLuigi Ballabio and Goutham Balaraman
Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.
