If you are looking for a book about data mining that provides practical solutions accompanied by a step-by-step explanation of the theory, “Data Mining with Python Theory, Application, and Case Studies” is what you are looking for. This book puts you in the driver’s seat of data mining and helps you with the tools to undertake the required voyage and discover patterns in data.
Carrying out the data mining process meticulously, this book introduces you to the ways of harvesting, compiling, evaluating and visualizing big data with Python packages. Throughout the process, interactive tutorials are featured, which means you will practice the material besides learning it, making it both interesting and efficient.
This book, ‘Data Mining with Python Theory, Application, and Case Studies,’ enriches the approach to data mining by explaining the principles and offering case studies. From the student's perspective, whoever wants to learn data mining as a data scientist or a business analyst will understand why it is important and how to use it in your projects.
Data Mining with Python Theory, Application, and Case Studies Table of Contents:
- Section I
- Data Wrangling
- Data Collection
- Data Integration
- Data Statistics
- Data Visualization
- Data Preprocessing
- Section II
- Data Analysis
- Classification
- Regression
- Clustering
- Frequent Patterns
- Outlier Detection
Who is this course for?
- It is considered relevant for students who want to study data mining concepts by utilizing Python.
- There are many different audiences and uses; the two main ones are Data scientists interested in broadening their knowledge and skills in data mining.
- Professionals dealing with business analysis can make use of data mining for insights and to support their decisions.
