发表于2024-06-16
Guide to Intelligent Data Analysis 2024 pdf epub mobi 电子书
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...
评分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...
评分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...
评分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...
评分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...
图书标签: 数据挖掘 数据分析 机器学习 计算机 MachineLearning 编程 实践 分析
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.
Overview of the data analysis process. Some pitfalls in each step, e.g. data quality.
评分Overview of the data analysis process. Some pitfalls in each step, e.g. data quality.
评分教材,只看了考试要求的1-9章,也没有通读,这本书基于crisp-dm框架写的,不是技术和算法书,对数据科学的理论部分讲解很多,适合理解数据科学的业务实践和思考方式。
评分完整的数据挖掘流程。7-9的算法部分还是太简略了,可以从其他机器学习、数据挖掘的书中弥补。
评分教材,只看了考试要求的1-9章,也没有通读,这本书基于crisp-dm框架写的,不是技术和算法书,对数据科学的理论部分讲解很多,适合理解数据科学的业务实践和思考方式。
Guide to Intelligent Data Analysis 2024 pdf epub mobi 电子书