100 Best Big Data Books of All Time

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Ma

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Build semantic knowledge systems with trusted and AI-ready taxonomies, ontologies, and knowledge graphs.Ontology Pipeline gives data leaders, semantic engineers, ontologists, taxonomists, knowledge managers, librarians, AI architects, and enterprise data teams a practical framework for turning messy organizational language into structured, machine-readable knowledge. Instead of treating ontology d

Get the eBook free when you register your print book at Manning."An exceptional deep dive into the next frontier of AI.”—Aman Chadha, GoogleThis book is a practical guide to understanding how modern reasoning-oriented LLMs work by building their core methods step by step. The book tells a clear engineering story: start with a conventional pre-trained LLM, learn how text generation works, build rel

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.Author

Master Excel faster, work smarter, and build skills that last.If you’ve ever felt intimidated by formulas, spreadsheets, or the many features packed into Excel, this book was made for you. The Excel Complete Course 2026 breaks everything down into clear, visual, step-by-step lessons that help you build practical Excel skills quickly and confidently.Whether you’re learning for work, school, busines

In The Second Machine Age MIT's Erik Brynjolfsson and Andrew McAfee—two thinkers at the forefront of their field—reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.

Amid this bounty will also be wrenching change. Professions of all kinds—from lawyers to truck drivers—will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.

Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.

A fundamentally optimistic book, The Second Machine Age will alter how we think about issues of technological, societal, and economic progress.

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Observability is the only way to engineer, manage, and improve the business-critical systems that customers depend on every day—and as the complexity of software grows, so does the need for observability. With this thoroughly revised second edition, authors Charity Majors, Liz Fong-Jones, and George Miranda take inventory of the current state of the field and explain how practitioners can evolve t

Essential Structured Query Language (ANSI SQL-99) six page laminated guide with core commands, statements, syntax and terms for support of beginners who are learning, and experts as a handy quick reference. Author Robin Nixon worked with computers in the 80s and started developing websites in the 90s becoming an expert and writing over 40 programming books and over 500 articles for top computer ma

Analyze data like a pro, even if you’re a beginner.Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. Anthony DeBarros, a journalist and data analyst, focuses on using SQL to find the story within your data. The examples and code use the open-source databas

Query and modify data effectively with the latest T-SQL featuresMaster Transact-SQL's fundamentals, and write correct, robust code for querying and modifying data with modern Microsoft data technologies, including SQL Server 2022, Azure SQL Database, and Azure SQL Managed Instance. Long-time Microsoft Data Platform MVP Itzik Ben-Gan explains key T-SQL concepts, helping you apply your knowledge wit

Build and deploy AI-driven trading systems using the 7-Stage workflow with pandas, Polars, LightGBM, PyTorch, Optuna, zipline-reloaded, MLflow, Feast, and SHAPKey FeaturesBuild point-in-time pipelines, integrate alternative data, and ensure data integrityBuild and validate predictive models using GBMs, Transformers, and causal inference frameworks to create robust, interpretable alpha signalsDeplo