圖書標籤: 機器學習 MachineLearning 數據挖掘 python 人工智能 Python 計算機科學 算法
发表于2024-06-01
Machine Learning in Action pdf epub mobi txt 電子書 下載 2024
It's been said that data is the new "dirt"—the raw material from which and on which you build the structures of the modern world. And like dirt, data can seem like a limitless, undifferentiated mass. The ability to take raw data, access it, filter it, process it, visualize it, understand it, and communicate it to others is possibly the most essential business problem for the coming decades.
"Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. By implementing the core algorithms of statistical data processing, data analysis, and data visualization as reusable computer code, you can scale your capacity for data analysis well beyond the capabilities of individual knowledge workers.
Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, you'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.
As you work through the numerous examples, you'll explore key topics like classification, numeric prediction, and clustering. Along the way, you'll be introduced to important established algorithms, such as Apriori, through which you identify association patterns in large datasets and Adaboost, a meta-algorithm that can increase the efficiency of many machine learning tasks.
Peter Harrington holds Bachelors and Masters Degrees in Electrical Engineering. He worked for Intel Corporation for seven years in California and China. Peter holds five US patents and his work has been published in three academic journals. He is currently the chief scientist for Zillabyte Inc. Peter spends his free time competing in programming competitions, and building 3D printers.
over simplified in maths, you do need refer to other textbooks for get better idea how it works. and too much coding details, I can understand as the author was from CS background, but I think you need read more, beside this is indeed a nice start point.
評分理論條理清楚、舉重若輕。可惜程序代碼水平稍差。
評分看這書可以同時入門機器學習,python,mapreduce,作者可以幾個方麵都講清楚,真不容易
評分Bad Smells in Codes...
評分沒學習又想學機器學習的可以考慮從這本書入手。偏嚮於應用的一本不錯的入門書
客观说,完全不能当入门书。 缺少必要的证明过程,有些甚至连公式都没有。 我觉得既然要学习机器学习,光改改代码完全是不够的,起码还得知道各个算法的基本公式和过程,不幸的是,这本书没有。 就比如逻辑斯蒂回归那章,他连损失函数都没提,就开始说梯度法了。问题是梯度法的...
評分我的学习过程如下,供大家参考: 1、有些python的基础编程能力,如果没有,先花半个小时学习下; 2、数学基本统计基础,如果不懂数学原理,可以先不要去理解数学原理; 3、先上手写下代码,沉浸进入,熟悉了代码流程,再回头去看数据原理,就明白了。 5、一句话,先不求甚解,...
評分 評分纯属好奇机器学习是怎么回事,虽然是coding渣,冲着现在三分热情在慕课上补了下python的基础知识。就跑来看实战。 下了kiddle版和pdf版本的看了第一章节,大学的矩阵相加,相减,相乘都忘光了, numpy的各个函数也不熟。看的很打击积极性。 遂又上51cto上 又搜机器学习的相关...
評分机器学习是人工智能研究领域中一个极其重要的研究方向,在现今的大数据时代背景下,捕获数据并从中萃取有价值的信息或模式,成为各行业求生存、谋发展的决定性手段,这使得这一过去为分析师和数学家所专属的研究领域越来越为人们所瞩目。 本书第一部分主要介绍机器学习基础,以...
Machine Learning in Action pdf epub mobi txt 電子書 下載 2024