A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about t…
Shelve Hands-On Machine Learning with Scikit-Learn and TensorFlow
Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and opti…
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged …
Shelve An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this…
Shelve Data Science from Scratch: First Principles with Python
A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics.
Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing i…
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, w…
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with dat…
Shelve Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
During the past decade there has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marke…
Shelve The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data …
Shelve Natural Language Processing with Transformers: Building Language Applications with Hugging Face
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data …
Shelve Python Data Science Handbook: Essential Tools for Working with Data
Even bad code can function. But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code…
Shelve Clean Code: A Handbook of Agile Software Craftsmanship
An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to …
Shelve Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People
Don't simply show your data — tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of…
Shelve Storytelling with Data: A Data Visualization Guide for Business Professionals
For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduct…
Straight from the programming trenches, The Pragmatic Programmer cuts through the increasing specialization and technicalities of modern software development to examine the core process--taking a …
Shelve The Pragmatic Programmer: From Journeyman to Master
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results i…
Shelve Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD
In this "important and comprehensive" guide to statistical thinking ( New Yorker ), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems.
…
Shelve The Art of Statistics: How to Learn from Data
Dr. Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.
In AI Superpowers, Kai-Fu Lee…
Shelve AI Superpowers: China, Silicon Valley, and the New World Order
Python's simplicity lets you become productive quickly, but this often means you aren't using everything it has to offer. With this hands-on guide, you'll learn how to write effective, idiomatic Pytho…
Shelve Fluent Python: Clear, Concise, and Effective Programming
Python Crash Course is a fast-paced, thorough introduction to programming with Python that will have you writing programs, solving problems, and making things that work in no time.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make …
Shelve R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
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'l…
Shelve Fundamentals of Data Engineering: Plan and Build Robust Data Systems
Nobel laureate Richard H. Thaler has spent his career studying the radical notion that the central agents in the economy are humans—predictable, error-prone individuals. Misbehaving is his arresting, …
Shelve Misbehaving: The Making of Behavioral Economics
This book is meant to help the reader learn how to program in C. It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a wor…
If you've ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?
In "Automate…
Shelve Automate the Boring Stuff with Python: Practical Programming for Total Beginners
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. Th…
Shelve Mathematics for Machine Learning: 1st Edition
The design patterns in this book capture best practices and solutions to recurring problems in machine learning. Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-a…
Shelve Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Concise and to the point — the book can be read during a week. During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent ye…
