Description
Hands-on Scikit-Learn for Machine Learning Applications is a very practical guide to entering the world of data science and machine learning using the popular Scikit-Learn library in Python. Using a project-based approach, the author walks the reader through all the steps of a data mining project, from loading and preprocessing data to implementing complex algorithms.
The text is structured to explain concepts such as classification, regression, and clustering with real-world examples. This is an ideal resource for those who want to quickly implement intelligent models without getting too involved in pure mathematics.
Book Features
- Step-by-step tutorial on working with key Scikit-Learn functions for data analysis.
- Complete coverage of supervised and unsupervised learning topics.
- Providing feature engineering techniques to improve model performance.
- Focus on evaluating models using rigorous statistical criteria.
- Suitable for beginners and analysts looking to quickly learn data science tools.
Book specifications
- Publisher: Apress
- Instructor/Author: David Paper
- Number of pages: 247
- Number of chapters: 8
- 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
2.2 MB
