Indian Institute of Information Technology, Allahabad
Department of Information Technology
Course Syllabus a Template
1. Name of the Course: Introduction to Machine Learning
2. LTP structure of the course: 2-1-1
3. Objective of the course: This course gives an introduction to machine learning. It is about unified understanding of the models and algorithms used in machine learning.
4. Outcome of the course: Students will be able to understand basic concept and they will be able to successfully apply it on real data set.
5. Course Plan:
Topics for Coverage
Decision Trees and K-Nearest-Neighbors, Bias- Variance decomposition, Linear Regression, Perceptron, Logistic Regression, Support Vector Machines (SVM), Kernels and nonlinear SVMs.
Model Selection, Feature Selection, Ensemble Methods, Gaussian Mixture Models. Hierarchical and Flat Clustering,
Linear Dimensionality Reduction, Matrix Factorization, Nonlinear Dimensionality Reduction and Manifold Learning,
Artificial Neural Network (Forward/Back propagation);
6. Text Book: Christopher Bishop, “Pattern recognition and machine learning”, Springer, 2007.Richard