Ultimate Machine Learning Algorithms with Python
Language: English
Published by Orange Education Pvt Ltd, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 56.65
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Learn the Algorithms Powering Modern AI. Build the Intelligence Behind Real-World Decisions.Book DescriptionUltimate Machine Learning Algorithms with Python bridges the gap between mathematical understanding and practical implementation, presenting every major algorithm with both theoretical rigour and plain-language intuition, so that readers at any level can build real-world competence.You begin with supervised learning fundamentals - linear and logistic regression, decision trees, SVMs, and neural networks - before advancing to ensemble methods including Random Forests, XGBoost, and CatBoost. The book then moves into unsupervised learning through clustering, dimensionality reduction, and anomaly detection, with evaluation methods covered in depth for both paradigms. Every algorithm is grounded in a Python implementation using scikit-learn and industry-standard tooling.What you will learn¿ Apply supervised learning algorithms to regression and classification problems.¿ Implement clustering and dimensionality reduction for unsupervised tasks.¿ Build ensemble models using Random Forests, XGBoost, and CatBoost.¿ Evaluate models using appropriate metrics for each algorithm type.¿ Develop end-to-end projects in fraud detection and recommendation systems.¿ Select, tune, and explain ML models for real business problems.Table of Contents1. Introduction to Machine Learning Algorithms2. Regression Algorithms3. Classification Algorithms4. Ensembling Methods5. Evaluation Methods for Supervised Learning Algorithms6. Clustering Algorithms7. Dimensionality Reduction8. Evaluation Methods for Unsupervised Learning Algorithms9. Building Recommender Systems10. Building Anomaly Detection System11. Building Spam Email Classification12. Conclusion and Future Trends Index.…
Seller Inventory # 9789349887329
- Title
- Ultimate Machine Learning Algorithms with Python
- Author
- Ritesh Ratti
- Publisher
- Orange Education Pvt Ltd
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 9349887320
- ISBN 13
- 9789349887329
- Item weight
- 701 grams
- Dimensions
- 235x191x20 mm
Learn the Algorithms Powering Modern AI. Build the Intelligence Behind Real-World Decisions.
Book Description
Ultimate Machine Learning Algorithms with Python bridges the gap between mathematical understanding and practical implementation, presenting every major algorithm with both theoretical rigour and plain-language intuition, so that readers at any level can build real-world competence.
You begin with supervised learning fundamentals - linear and logistic regression, decision trees, SVMs, and neural networks - before advancing to ensemble methods including Random Forests, XGBoost, and CatBoost. The book then moves into unsupervised learning through clustering, dimensionality reduction, and anomaly detection, with evaluation methods covered in depth for both paradigms. Every algorithm is grounded in a Python implementation using scikit-learn and industry-standard tooling.
What you will learn
● Apply supervised learning algorithms to regression and classification problems.
● Implement clustering and dimensionality reduction for unsupervised tasks.
● Build ensemble models using Random Forests, XGBoost, and CatBoost.
● Evaluate models using appropriate metrics for each algorithm type.
● Develop end-to-end projects in fraud detection and recommendation systems.
● Select, tune, and explain ML models for real business problems.
Table of Contents
1. Introduction to Machine Learning Algorithms
2. Regression Algorithms
3. Classification Algorithms
4. Ensembling Methods
5. Evaluation Methods for Supervised Learning Algorithms
6. Clustering Algorithms
7. Dimensionality Reduction
8. Evaluation Methods for Unsupervised Learning Algorithms
9. Building Recommender Systems
10. Building Anomaly Detection System
11. Building Spam Email Classification
12. Conclusion and Future Trends
Index
"Synopsis" may belong to another edition of this title.
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last update: 01/06/2022
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last updated: 01/06/2022