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A machine learning from Bayesian perspective, different from deep learning approach

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 book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch., If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out., Get a crash course in Python, Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science, Collect, explore, clean, munge, and manipulate data, Dive into the fundamentals of machine learning, Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering, Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Common Lisp Recipes is a collection of solutions to problems and answers to questions you are likely to encounter when writing real-world applications in Common Lisp. Written by an author who has used Common Lisp in many successful commercial projects over more than a decade, this book is the first Common Lisp book which covers areas as diverse as web programming, databases, graphical user interfaces, communication with other programming languages, multi-processing, and mobile devices as well as debugging techniques and optimization, to name just a few. It is organized around specific problems or questions each followed by ready-to-use example solutions and clear explanations of the concepts involved, plus pointers to alternatives and more information. Each recipe can be read independently of the others and thus the book will hopefully earn a special place on your bookshelf as a reference work you always want to have within reach. Common Lisp Recipes is aimed at programmers who are already familiar with Common Lisp to a certain extent but do not yet have the experience you typically only get from years of hacking in a specific computer language. It is written in a style that mixes hands-on no-frills pragmatism with precise information and prudent mentorship. If you feel attracted to Common Lisp's mix of breathtaking features and down-to-earth utilitarianism, you'll also like this book.

Classical C Programming Book, everyone should read it