Machine Learning Foundation Algorithm and Applications

Author : Dr. Prachi Chhabra, Dr. Ujwala Thakur, Dr. Geeta, Ms. Lopamudra Mohanty

Machine Learning: Foundations, Algorithms and Applications is a book that introduces the fundamental concepts of Machine Learning.
It explains how machines learn patterns from data and make predictions or decisions.
The book covers important learning approaches such as supervised, unsupervised, and reinforcement learning.
It discusses popular algorithms such as Linear Regression, Decision Trees, K-NN, SVM, and clustering.
The book also explains the mathematical and statistical foundations required for Machine Learning.
It provides an understanding of model training, testing, validation, and performance evaluation.
Different techniques for improving model accuracy and avoiding overfitting are discussed.
The book connects theoretical concepts with practical Machine Learning applications.
Applications may include classification, prediction, recommendation, image processing, and data analysis.
Overall, it serves as a useful foundation for students and beginners who want to understand and apply Machine Learning.