Books

Get a solid foundation in machine learning and learn practical applications of LLM-based applications.

Ideas for projects when teaching Python as well as general inspiration ex. when building a hobby project. It sources use-cases from Reddit and is grouped in some 20 chapters.

Discover how Java developers can contribute to a sustainable future. Written by Java Champions and community experts, this collaborative guide explores practical approaches to sustainable software engineering, from resource-efficient design to mindful architecture, empowering you to reduce your environmental impact while building better systems.

Falling In (and out of) Love (and lust) is a debut poetry pamphlet themed around love and relationships. It explores diverse emotional aspects of intimacy from euphoria to heartbreak, inviting us to consider not only what it means to love another but, crucially, to love oneself.

Working with Go effectively, requires proficiency and understanding beyond learning the simple syntax. It can take developers months or even years to acquire this experience, especially those coming from OOP. This book sets out to short-circuit that process and get you there faster! Includes Generics.

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.

Scientific Art is an artistic movement about art and science.

This book contains both pure Clojure examples as well as examples using Java libraries built in my book https://leanpub.com/javaai/ and OpenAI APIs.

Develop insights from data with tidy tools. Import, wrangle, visualize, and model data with the Tidyverse R packages.

Reading "Learn Python the Simple Way", you'll learn how software work.At this moment, Python is one of the fundamental programming languages for Machine Learning (ML), Scientific and Numeric Computing, Robotics and even Web Development.

Die Domain-driven Design Referenz gibt einen Überblick über die grundlegenden Pattern für Domain-driven Design. Domain-driven Design ist ein Ansatz für die Architektur und das Design von Software-Projekten, das sich konsequent nach den fachlichen Anforderungen richtet..Die Referenz wurde vom Erfinder von DDD, Eric Evans, in Englischverfasst.

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.

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

This book teaches the fundamental concepts and tools behind reporting modern data analyses in a reproducible manner. As data analyses become increasingly complex, the need for clear and reproducible report writing is greater than ever. The material for this book was developed as part of the industry-leading Johns Hopkins Data Science Specialization. Printed versions are available through Lulu (see link below).

Quer aprender Ruby de uma maneira bem direto ao ponto? Esse é o livro que você estava procurando.