ML书籍推荐

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Kai Hwang, Min Chen

评分 暂无

The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To tha

Machine Learning System Design Interview

Ali Aminian, Alex Xu

评分 9.3分

Machine learning system design interviews are the most difficult to tackle of all technical interview questions. This book provides a reliable strategy and knowledge base for approaching a broad range

Hands-On Reinforcement Learning with Python

Sudharsan Ravichandiran

评分 暂无

Learn Understand the basics of reinforcement learning methods, algorithms, and elements Train an agent to walk using OpenAI Gym and Tensorflow Understand the Markov Decision Process, Bellman’s optimal

Scikit-Learn、Keras和TensorFlow的机器学习实用指南(第2版)(影印版)

[美] Geron Aurelien

评分 暂无

通过具体的例子、很少的理论以及成熟的Python框架：Scikit-Learn、keras和TensorFlow，作者Aurélien Géron通过本书帮助读者掌握构建智能系统所需要的概念和工具。读者从中将会学习到各种技术，从简单的线性回归及发展到深度神经网络。每章的练习有助于读者运用所学到的知识，只需要有一些编程经验就行了。

Fundamentals of Machine Learning for Predictive Data Analytics

John D. Kelleher, Brian Mac Namee, Aoife D'Arcy

评分 7.3分

Python Machine Learning

Sebastian Raschka

评分 8.4分

About This Book Leverage Python' s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize m

Hands-On Machine Learning with Scikit-Learn and TensorFlow

Aurélien Géron

评分 9.2分

The Little MLer

Matthias Felleisen, Daniel P. Friedman, Duane Bibby, Robin Milner

评分 8.4分

The book, written in the style of The Little Schemer, introduces instructors, students, and practicioners to type-directed functional programming. It covers basic types, quickly moves into datatypes,

Neural Network Learning

Martin Anthony, Peter L. Bartlett

评分 暂无

This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistica

Neural Networks for Applied Sciences and Engineering

Samarasinghe, Sandhya

评分 暂无

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scient

The EM Algorithm and Extensions

McLachlan, Krishnan

评分 暂无

在线阅读本书 The EM Algorithm and Extensions remains the only single source to offer a complete and unified treatment of the theory, methodology, and applications of the EM algorithm. The highly applied ar

ML程序设计教程

[英] Lawrence C. Paulson

评分 8.7分

本书是关于ML程序设计的经典教材，详细介绍如何使用ML语言进行程序设计，并讲解函数式程序设计的基本原理。 书中含有大量例子，涵盖了排序、矩阵运算、多项式运算等方面。大型的例子包括一个一般性的自顶向下语法分析器、一个一演算归约程序和一个定理证明机。书中也讲述了关于数组、队列、优生队列等高效的函数式实现，并且有一章专门讨论函数式程序的形式论证。本书的代码均可以从作者网站（http://www.cl.c