Machine Learning, 2E
Price: 795.00 INR
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ISBN:
9789367252901
Publication date:
01/04/2026
Paperback
600 pages
184x240mm
Price: 795.00 INR
We sell our titles through other companies
Disclaimer :You will be redirected to a third party website.The sole responsibility of supplies, condition of the product, availability of stock, date of delivery, mode of payment will be as promised by the said third party only. Prices and specifications may vary from the OUP India site.
ISBN:
9789367252901
Publication date:
01/04/2026
Paperback
600 pages
Second Edition
S. Sridhar & M. Vijayalakshmi
The Second Edition of the Machine Learning is a substantial upgrade, reflecting the rapid evolution of the field in recent years. It is intended as an introductory textbook employing a clear algorithmic approach and numerical examples to explain machine learning concepts. The content is
designed for undergraduate and postgraduate students in Computer Science, Information Technology and related engineering disciplines. It is also suitable for learners in data science, data analytics and data mining.
A new chapter has been added in this edition to deepen readers' understanding of the mathematical foundations essential for machine learning. Two additional chapters introduce data preparation and
feature engineering, along with exploratory data analysis. The book also offers supplementary online theoretical material and a laboratory manual, accessible through QR codes placed within the relevant sections. The laboratory component includes 25 Python-based experiments and case studies designed to provide hands-on experience with machine learning techniques.
Rights: World Rights
Second Edition
S. Sridhar & M. Vijayalakshmi
Description
Uses only minimal mathematics to understand the machine learning algorithms covered in the book
• Follows an algorithmic approach to explain the basics of machine learning
• Comes with various numerical problems to emphasize on the important concepts of data analytics
• Includes a laboratory manual for implementing machine learning concepts in Python environment
• Has two appendices covering the basics of Python and Python packages
• Focuses on pedagogy like chapter-end review and numerical questions, crosswords and jumbled word searches
• Illustrates important and latest concepts like concept learning, regression analysis, decision tree learning, probabilistic graphical models, artificial neural networks, support vector machines, ensemble learning, cluster analysis and deep learning
Second Edition
S. Sridhar & M. Vijayalakshmi
Description
Uses only minimal mathematics to understand the machine learning algorithms covered in the book
• Follows an algorithmic approach to explain the basics of machine learning
• Comes with various numerical problems to emphasize on the important concepts of data analytics
• Includes a laboratory manual for implementing machine learning concepts in Python environment
• Has two appendices covering the basics of Python and Python packages
• Focuses on pedagogy like chapter-end review and numerical questions, crosswords and jumbled word searches
• Illustrates important and latest concepts like concept learning, regression analysis, decision tree learning, probabilistic graphical models, artificial neural networks, support vector machines, ensemble learning, cluster analysis and deep learning
S. Sridhar and M. Vijayalakshmi
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