SDP on Introduction to Machine Learning
Resource Person : Mrs.T.Subha, Associate Professor/IT, SSEC
Date : 17th FEB – 22nd FEB 2020
Time : 10.00 AM to 04.00 PM
Venue : CSE Seminar Hall
Target Participants : CSE Students and Faculties (Around 170 Participants)
Topics covered :
- Introduction to Linear Algebra, Machine Learning and its use in research, Overview of Machine Learning, Utility, classification of ML systems, example of applications
- Introduction to Jupyter Notebook and Google Colab
- Supervised vs. Unsupervised Learning, Linear Regression with one variable (and any associated topic).
- Introduction to Python, NumPy and Pandas
- Gradient Descent
- Data visualization, Data pre-processing (handling missing data, data cleaning, transformation), Implementation of Gradient Descent
- Linear Regression with multiple variables
- few examples of Linear Regression using Python
- Logistic Regression
- few examples of Logistic Regression using Python
- Good Practices in Machine Learning (Special Session) Participants will be given time to prepare assignment
