An Introduction To Data Analysis

An Introduction To Data Analysis

It is just the initial step, be that as it may, which is the reason the accompanying parts will examine all that you want to be familiar with information examination overall and prescient investigation explicitly. This implies there are nitty-gritty sections on information gathering, information mining, relapse methods, AI strategies, discrete decision models, and that's just the beginning. You will likewise observe a top to bottom glance at a significant number of the most widely recognized slip-ups that organizations make with regards to information the executives and how to keep away from them. At last, things will wrap up with a point-by-point conversation of the best open-source programs that can make them examine information this very evening. Inside you will find: -A Complete Breakdown of the Basics of Data Analytics and Predictive Analysis -The Secrets the Pros Use When It Comes to Data Mining and Data Gathering -Information Management Mistakes to Avoid -The Best Beginner Regression and Machine Learning Techniques -The Best Free Programs to Get You Started -What's more a whole lot more...

An Introduction to Statistical Methods and Data Analysis

A General Introduction to Data Analytics

A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.