Bpb Publications
Machine Learning for Beginners: Learn to Build Machine Learning Systems Using Python (English Edition)
Key Metrics
- Harsh Bhasin
- Bpb Publications
- Paperback
- 9789389845426
- 9.25 X 7.52 X 0.55 inches
- 1.01 pounds
- Computers > Data Science - Data Visualization
- English
Secure TransactionBook Description
Key Features
Description
This book covers important concepts and topics in Machine Learning. It begins with Data Cleansing and presents an overview of Feature Selection. It then talks about training and testing, cross-validation, and Feature Selection. The book covers algorithms and implementations of the most common Feature Selection Techniques. The book then focuses on Linear Regression and Gradient Descent. Some of the important Classification techniques such as K-nearest neighbors, logistic regression, Na�ve Bayesian, and Linear Discriminant Analysis are covered in the book. It then gives an overview of Neural Networks and explains the biological background, the limitations of the perceptron, and the backpropagation model. The Support Vector Machines and Kernel methods are also included in the book. It then shows how to implement Decision Trees and Random Forests.
Towards the end, the book gives a brief overview of Unsupervised Learning. Various Feature Extraction techniques, such as Fourier Transform, STFT, and Local Binary patterns, are covered. The book also discusses Principle Component Analysis and its implementation.
What will you learn
Who this book is for
The book is designed for Undergraduate and Postgraduate Computer Science students and for the professionals who intend to switch to the fascinating world of Machine Learning. This book requires basic know-how of programming fundamentals, Python, in particular.
Table of Contents
1. An introduction to Machine Learning
2. The beginning: Pre-Processing and Feature Selection
3. Regression
4. Classification
5. Neural Networks- I
6. Neural Networks-II
7. Support Vector machines
8. Decision Trees
9. Clustering
10. Feature Extraction
Appendix
A1. Cheat Sheets
A2. Face Detection
A3.Biblography
About the Author
Harsh Bhasin is an Applied Machine Learning researcher. Mr. Bhasin worked as Assistant Professor in Jamia Hamdard, New Delhi, and taught as a guest faculty in various institutes including Delhi Technological University. Before that, he worked in C# Client-Side Development and Algorithm Development.
Mr. Bhasin has authored a few papers published in renowned journals including Soft Computing, Springer, BMC Medical Informatics and Decision Making, AI and Society, etc. He is the reviewer of prominent journals and has been the editor of a few special issues. He has been a recipient of a distinguished fellowship.
Outside work, he is deeply interested in Hindi Poetry, progressive era; Hindustani Classical Music, percussion instruments.
His areas of interest include Data Structures, Algorithms Analysis and Design, Theory of Computation, Python, Machine Learning and Deep learning.
Your LinkedIn Profile:
https: //in.linkedin.com/in/harsh-bhasin-69134426
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