TY  - BOOK
AU  - Kalita ,Jugal 
TI  - Machine Learing: Theory and Practice 
SN  - 9780367433543
U1  - 006.31 
PY  - 2023///
CY  - New York
PB  - CRC Press, 
KW  - Machine Learning
KW  - Ensemble learning
KW  - Explanation-based learning
KW  - Artificial Intelligence
KW  - Machine theory
N1  - Include Bibliography and Indexes
N2  - Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples
ER  -