According to New Revised CBCS Syllabus w.e.f. 2020-21
A Text book of
Author: Neeta Nandgude, Dr. Poonam Ponde
ISBN: 978-93-90646-02-9
Machine Learning (ML) is a subject dedicated to information and constructing techniques that 'learn', that is, techniques that use facts to perform tasks. It is a type of artificial intelligence that makes predictions without actually being programmed to do so. Machine mastering algorithms have many applications, such as medicine, e mail filtering, speech recognition, and computer vision, where it's hard or not feasible to use traditional algorithms to carry out the desired tasks.
This textbook, authored by eminent teachers in the field, is designed to make the subject easy to understand and grasp. It uses a variety of techniques such as simple language, learning aids, etc., with the aim of helping students of M.Sc. (Comp. Science) Sem. III.
1. Introduction to Machine Learning
1. Introduction
2. Concepts
3. Basics of Machine Learning
4. Statistics
5. Handling Datasets
2. Machine Learning Models
1. Introduction
2. Type of Learning
3. Components of Generalization Error
4. A Learning System Cycle and Design Cycle
5. Metrics for Evaluation
6. Classification Accuracy and Performance
3. Regression Models
1. Introduction
2. Linear Regression
3. Non-linear Regression
4. Classification Models
1. Introduction
2. K – Nearest Neighbors (KNN)
3. Logistic Regression
4. Naïve Bayes Classification
5. Support Vector Machine
6. Decision Tree Classification
7. Python implementation of decision tree classification
8. Random Forest Classification
9. Comparison
5. Clustering Models
1. Introduction
2. Partitional Clustering
3. Hierarchical Clustering
6. Association Rules
1. Introduction
2. Key Terms
3. Apriori Algorithm
7. Reinforcement Learning
1. Introduction
2. Upper Confidence Bound (UCB)
3. Thompson Sampling
4. Q-Learning
8. Deep Learning
1. Introduction
2. Artificial Neural Network (ANN)
3. Convolution Neural Network (CNN)
4. Recurrent Neural Network (RNN)
According to New Revised CBCS Syllabus w.e.f. 2020-21
A Text book of
Author: Neeta Nandgude, Dr. Poonam Ponde
ISBN: 978-93-90646-02-9
Machine Learning (ML) is a subject dedicated to information and constructing techniques that 'learn', that is, techniques that use facts to perform tasks. It is a type of artificial intelligence that makes predictions without actually being programmed to do so. Machine mastering algorithms have many applications, such as medicine, e mail filtering, speech recognition, and computer vision, where it's hard or not feasible to use traditional algorithms to carry out the desired tasks.
This textbook, authored by eminent teachers in the field, is designed to make the subject easy to understand and grasp. It uses a variety of techniques such as simple language, learning aids, etc., with the aim of helping students of M.Sc. (Comp. Science) Sem. III.
