Python Machine Learning 在线电子书 图书标签: 机器学习 Python MachineLearning 计算机 python 数据分析 ML 数据挖掘
发表于2024-11-22
Python Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024
只看了 supervised learning 部分,很实用
评分说起来 Python 哥这学期到本校统计系了。。。
评分工程化相关章节蛮不错的,推荐~
评分按照上面的做 可以学到很多python2和python3的不兼容点 这个是最后使用pyTorch的 不是tensorflow 按照自己的需求下
评分嘴上说着不要还是勉强翻完了。很失望,大段代码和前后不搭的实例缺少完善的理论框架而且不系统,编写太随意难得要领。不过还是姑且有些有用内容,不算太亏。
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.
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。
评分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...
评分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...
评分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...
评分但是是有前提的: 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。
Python Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024