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2024-10-05
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.
內容比較基礎,有py代碼,對著看比較容易理解。
評分書中介紹瞭“十大機器學習算法”中的八種,雖然不深入但是講解清楚容易理解和上手,是本佳作。從覆蓋麵上來看沒涉及到隨機森林算法和神經網絡是一個小遺憾。
評分讀瞭LR,ada boost,略讀瞭svm,psvm。數學渣子的福音,碼農最愛的實例。 雖然大傢都說寫的不好,不過入個門還是不錯。
評分讀它是為瞭熟悉Python語言;內容是在不敢恭維。
評分是本好書,有些章節還看的不是最明白。值得反復閱讀
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評分Python数据分析与机器学习实战 课程观看地址:http://www.xuetuwuyou.com/course/167 课程出自学途无忧网:http://www.xuetuwuyou.com 课程风格通俗易懂,真实案例实战。精心挑选真实的数据集为案例,通过python数据科学库numpy,pandas,matplot结合机器学习库scikit-lear...
Machine Learning in Action pdf epub mobi txt 電子書 下載 2024