Artificial Intelligence and Machine Learning detailed syllabus for Electronics & Communication Engineering (ECE) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the ECE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Electronics & Communication Engineering 8th Sem scheme and its subjects, do visit ECE 8th Sem 2019 regulation scheme. For Professional Elective-VI scheme and its subjects refer to ECE Professional Elective-VI syllabus scheme. The detailed syllabus of artificial intelligence and machine learning is as follows.
Course Objective:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.
Unit I
Introduction To Ai
Computerized reasoning – Artificial Intelligence (AI) – characteristics of an AI problem – Problem representation in AI – State space representation – problem reduction-Concept of small talk programming.
Unit II
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Unit III
Introduction To Machine Learning
Introduction to Machine Learning – Types of Machine learning – Basic Concepts in Machine Learning – SUPERVISED LEARNING :Linear Models for Classification: Discriminant Functions -Probabilistic Generative Models – Probabilistic Discriminative Models – Bayesian Logistic Regression. Neural Networks: Feed forward Network Functions – Error Backpropagation -Regularization in Neural Networks – Mixture Density Networks – Bayesian Neural Networks. Kernel Methods – Dual Representations – Radial Basis Function Networks – Ensemble learning: Boosting – Bagging.
Unit IV
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Unit V
Application
Examples of Machine Learning Applications – Linear Models for Regression – Linear Basis Function Models – The Bias-Variance Decomposition – Bayesian Linear Regression – Bayesian Model Comparison. Radar for target detection, Deep Learning Automated ECG Noise Detection and Classification, ML in Network for routing, traffic prediction and classification, Application of ML in Cognitive Radio Network (CRN).
Text Books:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
References:
- Patrick Henry Winston, “Artificial Intelligence”, Addison Wesley, 2000.
- Luger George F and Stubblefield William A, “Artificial Intelligence: Structures and Strategies for Complex Problem Solving”, Pearson Education, 2002.
- Christopher Bishop, “Pattern Recognition and Machine Learning” Springer, 2007.
- Kevin P. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2012.
- Ethem Alpaydin, “Introduction to Machine Learning”, MIT Press, 3rd Edition, 2014
- Sayed, A.H., 2014. Adaptation, learning, and optimization over networks. Foundations and Trends” in Machine Learning, 7(4-5), pp.311-801.
For detailed syllabus of all the other subjects of Electronics & Communication Engineering 8th Sem, visit ECE 8th Sem subject syllabuses for 2019 regulation.
For all Electronics & Communication Engineering results, visit Anna University ECE all semester results direct link.