This book provides a systematic overview and classification of tasks in data analysis, methods to solve them and typical problems encountered. Different views from classical and non-classical statistics like Bayesian inference and robust statistics, exploratory data analysis, data mining and machine learning are combined together to provide a better understanding of the methods, their potentials and limitations. Features: a Focuses on validation and pitfalls related to real world applications of these techniques a Presents different approaches, analysing their advantages and disadvantages for certain types of tasks including exploratory data analysis, data mining, classical statistics and robust statistics a Contains case studies and examples to enhance understanding a A supplementary website provides numerous hands-on examples This collective view of data analysis problems and methods, their potentials and limitations is an indispensable learning tool for graduate and advanced undergraduate students.
發表於2024-12-23
Guide to Intelligent Data Analysis 2024 pdf epub mobi 電子書 下載
Data analysis is the every day work for my PhD project, but I have no idea how to do it intelligently. In the past year, I just followed my supervisor's advice, like checking this attribute, and then do the scatter plot. Sometimes, I tried a little analys...
評分Data analysis is the every day work for my PhD project, but I have no idea how to do it intelligently. In the past year, I just followed my supervisor's advice, like checking this attribute, and then do the scatter plot. Sometimes, I tried a little analys...
評分Data analysis is the every day work for my PhD project, but I have no idea how to do it intelligently. In the past year, I just followed my supervisor's advice, like checking this attribute, and then do the scatter plot. Sometimes, I tried a little analys...
評分Data analysis is the every day work for my PhD project, but I have no idea how to do it intelligently. In the past year, I just followed my supervisor's advice, like checking this attribute, and then do the scatter plot. Sometimes, I tried a little analys...
評分Data analysis is the every day work for my PhD project, but I have no idea how to do it intelligently. In the past year, I just followed my supervisor's advice, like checking this attribute, and then do the scatter plot. Sometimes, I tried a little analys...
圖書標籤: 數據挖掘 數據分析 機器學習 計算機 MachineLearning 編程 實踐 分析
教材,隻看瞭考試要求的1-9章,也沒有通讀,這本書基於crisp-dm框架寫的,不是技術和算法書,對數據科學的理論部分講解很多,適閤理解數據科學的業務實踐和思考方式。
評分Overview of the data analysis process. Some pitfalls in each step, e.g. data quality.
評分剛到手,看瞭前麵幾章,完整的描述瞭如何做一個數據分析的過程。前麵150頁講瞭在建模前的一些工作,後麵150頁簡單的講瞭一些機器學習的model。最可貴的是每一章最後麵都簡單講瞭下如何用現有的工具(knime&R)實現這些方法。
評分教材,隻看瞭考試要求的1-9章,也沒有通讀,這本書基於crisp-dm框架寫的,不是技術和算法書,對數據科學的理論部分講解很多,適閤理解數據科學的業務實踐和思考方式。
評分教材,隻看瞭考試要求的1-9章,也沒有通讀,這本書基於crisp-dm框架寫的,不是技術和算法書,對數據科學的理論部分講解很多,適閤理解數據科學的業務實踐和思考方式。
Guide to Intelligent Data Analysis 2024 pdf epub mobi 電子書 下載