Data Science & AI Books


Representation Learning for Natural Language Processing, 2nd Edition

NLP

This open book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including

AI at the Edge

Linux

Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target-from ultra-low powe

Unlock Data Agility with Composable Data Architecture

Are your data systems slowing down your AI initiatives? The potential of AI to revolutionize business is undeniable, but many organizations struggle to bridge the gap between ambitious ideas and real-world results. The cause? Traditional data architectures remain too rigid and siloed to support today's dynamic, data-intensive demands. If you're a d

Understanding ETL

Extract, transform, load (ETL) is at the center of every application of data, from business intelligence to AI. Constant shifts in the data landscape - including the implementations of lakehouse architectures and the importance of high-scale real-time data - mean that today's data practitioners must approach ETL a bit differently. This updated tech

Intermediate Statistics with R

R Statistics

Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. Building on the basic statistical thinking emphasized in an introductory course, a second course in statistics at the undergraduate level can explore a large number of statistical methods. This text covers more advanced graphical su

Learning Analytics Methods and Tutorials

R

This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the latest in learning analytics and education data minin

Essential GraphRAG

A Retrieval Augmented Generation (RAG) system automatically selects and supplies domain-specific context to an LLM, radically improving its ability to generate accurate, hallucination-free responses. The GraphRAG pattern employs a knowledge graph to structure the RAG's input, taking advantage of existing relationships in the data to generate rich,

Delta Lake: The Definitive Guide

Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Pra

The AI Ladder

AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far adoption has been much slower than anticipated. With this practical report, business leaders will discover where they are in their AI journey and learn the steps they still need to take to implement an

Mastering Shiny

R Shiny

Master the Shiny web framework - and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visu