Course Title: Introduction to Machine Learning with Python
Class Schedule
The course length will be 8 weeks with two classes in each week and 3 hours in each class. The lecture plan of the course is as follows:
| Class# | Content |
|---|---|
| 1 |
Introduction to ML Python Basics (Environment setup, Variables, Loop, Array) |
| 2 |
Decision Tree Assignment 1 on Decision Tree |
| 3 | Python Basics (Function, Recursion, String, File) |
| 4 |
Linear Regression Logistic Regression |
| 5 | Python Basics (List, Dictionary, Numpy) |
| 6 |
Naive Bayes KNN, Text modeling |
| 7 |
Python Advanced (Pandas, Matplotlib) Introduction to scikit-learn |
| 8 |
Evaluation of Machine Learning Models (Cross-validation, overfitting, learning curve, over sampling/under sampling, etc.) |
| 9 | Assignment 1 Evaluation |
| 10 |
SVM Ensemble Learning Bagging Boosting |
| 11 |
Assignment 2 (on KNN, Naive Bayes, SVM, Regression) XGBoost |
| 12 | Unsupervised Learning |
| 13 |
Python Advanced (SciPy, Seaborn) Intro to WEKA |
| 14 | Introduction to ANN |
| 15 | Assignment 2 Evaluation |
| 16 | Final Exam |
Further Query
Email: iac@cse.buet.ac.bd
Phone: 9665650-80 Ext-6438, mobile : 01741 686742