Python Machine Learning pdf epub mobi txt 电子书下载 2025

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出版者:Packt Publishing - ebooks Account

作者:Sebastian Raschka

出品人:

页数:454

译者:

出版时间:2015-9

价格:USD 44.99

装帧:Paperback

isbn号码:9781783555130

丛书系列:

图书标签:

机器学习
Python
MachineLearning
计算机
python
数据分析
ML
数据挖掘
Python
机器学习
深度学习
数据科学
人工智能
编程
算法
神经网络
可视化
监督学习

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具体描述

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 machine learning systems and algorithms

Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets

Who This Book Is For

If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

What You Will Learn

Explore how to use different machine learning models to ask different questions of your data

Learn how to build neural networks using Keras and Theano

Find out how to write clean and elegant Python code that will optimize the strength of your algorithms

Discover how to embed your machine learning model in a web application for increased accessibility

Predict continuous target outcomes using regression analysis

Uncover hidden patterns and structures in data with clustering

Organize data using effective pre-processing techniques

Get to grips with sentiment analysis to delve deeper into textual and social media data

Style and approach

Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

作者简介

目录信息

读后感

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充其量不过是几个常用python ML包（scikit NumPy SciPy matplotlib pandas）的 cookbook 罢了。基本上每节的流程就是先告诉你一个ML概念大概是怎么回事，真的很大概，不过好处是至少会告诉你为什么要这么做。然后用一段示例代码告诉你这个东西在Python ML包里要调用哪几个接口...

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但是是有前提的： 1. 基础的线性代数知识需要大家温故知新一下； 2. 对于python中的numpy和pandas的一些基本操作需要熟悉； 3. 抽象能力，最好能把代数方程在大脑里映射出一个几何图形（最多三维）；只要有了以上的前提，读这本书还是挺靠谱的。

用户评价

评分☆☆☆☆☆

说实话这书没有想象中的好，它的定位是cookbook，对于ML的原理是有些阐述的，但是讲的不深，好多地方就是列出一个公式，让我这种数学渣看起来比较费劲，需要不断的查各种资料，对于400多页的书，也就能写到这种程度了。还有本书的typo是比较多的。本书的例子还好，ML的各方面都有涉及，对于入门是合适的。看完本书我觉得应该读一些理论方面的书，然后可以再速刷一遍，锻炼动手能力。最后两章还没读完，Deep Learning不好懂啊！

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还行吧，入门看看够了

评分☆☆☆☆☆

还行吧，入门看看够了

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实用性上还是不错的