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Machine Learning for Beginners - 2nd Edition
Paperback
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- Book Synopsis
- The second edition of "Machine Learning for Beginners" addresses key concepts and subjects in machine learning. The book begins with an introduction to the foundational principles of machine learning, followed by a discussion of data preprocessing. It then delves into feature extraction and feature selection, providing comprehensive coverage of various techniques such as the Fourier transform, short-time Fourier transform, and local binary patterns. Moving on, the book discusses principal component analysis and linear discriminant analysis. Next, the book covers the topics of model representation, training, testing, and cross-validation. It emphasizes regression and classification, explaining and implementing methods such as gradient descent. Essential classification techniques, including k-nearest neighbors, logistic regression, and naive Bayes, are also discussed in detail. The book then presents an overview of neural networks, including their biological background, the limitations of the perceptron, and the backpropagation model.
- About The Author
- Dr. Harsh Bhasin is a researcher and practitioner. Dr. Bhasin is currently associated with the Centre for Health Innovations, Manav Rachna International Institution of Research and Studies. Dr. Bhasin has completed his Ph. D. in Diagnosis and Conversion Prediction of Mild Cognitive Impairment Using Machine Learning from Jawaharlal Nehru University, New Delhi.
- Product Details
-
- ISBN
- 9789355515636
- Format
- Paperback
- Publisher
- BPB Publications, (16 October 2023)
- Number of Pages
- 384
- Weight
- 630 grams
- Language
- English
- Dimensions
- 240 x 190 x 20 mm
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