Assignments/seminars/notes.
StatsWithR notes: https://windy-cheque-98d.notion.site/Statistics-Notes-86f95e7c34c545388bb9d46a63fedfc8
Syllabus:
1. Measurement Scales, Populations and Samples
2. Central Limit Theorem, data exploration, basic distributions
3. Hypothesis Testing
4. Tests for categorial data
5. t-test and friends
6. Correlation and Regression
7. ANOVA
8. Checking Assumptions underlying ANOVA and linear regression
9. Linear Mixed Effects Models
10. Model Families and Logistic Regression
11. Model selection, Transformations, Power
Syllabus:
1. Linear Algebra
2. ML Basics
3. Feedforward NNs
4. Backpropogation
5. Regularization for deep learning
6. Optimization for training DNNs
7. Convolutional networks
8. Sequence modelling