Advanced Machine Learning Course

Statistical Inference

Basic Machine Learning Algorithms

1. Introduction to Advanced Machine Learning

2. Advanced Linear Regression

   1. Linear Regression Assumptions

   2. Ridge Regression

   3. Lasso Regression

3. SkLearn Pipelines

   1. Pipelines for KNN

   2. Encoding Techniques

   3. Scaling Techniques

4. Feature Engineering

   1. Transformations

   2. Feature Selection

   3. Bias Variance Tradeoff

5. Advance Decision Trees

   1. Pruning

   2. Best Features

   3. Hyper Parameter Tuning

6. Evaluation Metrics

1. 1. Classification Report

   2. LogLoss

7. Ensemble Techniques

1. Decision Tree Forests

2. Bagging Algorithms

3. Boosting Algorithms

8. Deep Learning Fundamentals

1. Backward Propagation

2. ANN and RNN Introduction

3. Keras for Classification

9. NLP Fundamentals

1. Understanding Bayesian Statistics

2. Bag of Words

3. Text Classification using TF-IDF

4. Introduction to Transformers

10. Model Deployment

1. Git Fundamentals

2. Saving and Loading Models

3. CI / CD Integration