Description
The book Applied Machine Learning introduces new algorithms and techniques in the field of machine learning, focusing on practical aspects and implementation. The author, moving away from purely theoretical, tries to turn the concepts of artificial intelligence into tangible tools for solving real-world problems in various industries. This work is designed for programmers and data scientists who want to deploy intelligent models in their business projects.
The second paragraph of the book is dedicated to examining the steps of data preparation, selecting appropriate supervised and unsupervised models, and finally evaluating the performance of the models. The learning process in this book is guided in such a way that the reader can discover hidden patterns in big data and implement data-driven decisions in his or her organization.
Book Features
- Focus on practical implementation of machine learning algorithms rather than pure theory
- Training various supervised and unsupervised learning models
- A step-by-step guide to data preprocessing and feature engineering
- Provide real-world examples of solving business challenges with AI
Book specifications
- Publisher: Springer
- Lecturer/Author: David Forsyth
- Number of pages: 496
- Number of chapters: 19
- Format: PDF
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File(s) password: www.downloadly.ir
File size
8.6 MB