Topics and Case Study

Linear Regression Topics

• LR Introduction
• LR Cost function
• Gradient descent Code
• Cross validation
• Regularisation
• Evaluation Metrics

Logistics Regression

• Logistic Regression Introduction
• Sigmoid Function
• Logistic Regression Cost function
• Gradient descent Code
• Cross validation
• Evaluation Metrics

Decision Tree

• Introductory code for DT
• Mathematical Intuition

Ensemble Techniques

• Bagging: Random Forest
• Boosting: GBDT, XGBoost, AdaBoost, CatBoost
• Stacking
• Cascading

Naive Bayes

• Mathematical Intuition
• Model Development
• Advantages and Disadvantages

Clustering

• K-Means
• Hierarchial
• GMM
• DBSCAN

Recommender System

• Apriori
• Content Based recommender System
• Collaborative filtering
• Matrix Factorization
• Evaluating RS

Time Series

• Forcasting
• Handling Missing Data and Anomalies
• Time Series decomposition
• Train Test Split and Measure of Forecast accuracy
• Simple Forcast Method
• Smoothing based methods
• Stationary
• ACF and PACF
• ARIMA Family and Facebook's Prophet