Description
The Python Data Mining Quick Start Guide is written with the aim of quickly and easily introducing those interested in the world of data analysis and data mining to the Python programming language. The author of the book explains the basic concepts of data mining in a very simple and fluent language so that even people with little experience in this field can easily relate to it and begin their learning path.
Throughout the chapters, the reader is introduced to the full data mining cycle, including data collection, cleaning, preprocessing, and finally extracting hidden patterns. Relying on popular Python libraries, the book teaches the audience how to transform raw, unstructured data into valuable, actionable insights for macro-management and business decisions.
Book Features
- A completely text-based and fast approach to entering the world of data mining without the need for a heavy mathematical background
- Practical, step-by-step training on cleaning data and preparing it for analytical processes
- Introducing and using standard and key Python tools and libraries in the field of data science
- Focus on extracting behavioral patterns, predictive analytics, and discovering valuable information from big data
- Providing concrete examples and small business projects to better understand theoretical concepts in practice
Book specifications
- Publisher: Packt
- Instructor/Author: Nathan Greeneltch
- Number of pages: 181
- Number of chapters: 7
- Format: PDF
Headlines
Pictures
User Guide
Extract the file and run it with the appropriate software.
Download link
File(s) password: www.downloadly.ir
File size
20 MB
