EGCO 623
Data Mining and Machine Learning
Data Mining and Machine Learning
Course Prerequisites
Basic Mathematics
Basic Statistics
Course Description
Concepts of data mining, data warehouse, data and data preprocessing, measures of similarity and dissimilarity, visualization, knowledge discovery from database, machine learning concept, supervised and unsupervised learning, inductive learning, decision tree learning, artificial neural networks, reinforcement learning, evolutionary algorithms, evaluating the performance of a classifier
Materials
All materials were moved to https://classroom.google.com/c/NTIzOTY5MzY2OTAz?cjc=vrplh2h
Association Analysis
Cluster Analysis
Visualization
Introduction to Machine Learning
Decision Tree, Random Forest, Bayes Learning, SVM
Neural Network and Deep Learning
Reinforcement Learning and Evolutionary Computation
Ensemble Methods
Model Evaluation
Machine Learning Software
Grading
Grades will be assigned on the following basis:
Midterm Exam 10 %
Final Exam 10 %
Assignments 30 %
Project 10 %
Attendance 40 %