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Overview
Course Introduction and What You Will Learn
How to Get Queries Resolved
Download Resources
Setup Environment
Python Setup - Local Installation
Python Setup - Google Colab
Packages Used
Understanding the data
Data Overview
Basic Data Stats
Course Review
Exploratory Data Analysis
Data Preprocessing Phase 1
Exploratory Data Analysis
Engineer new features and process data
Feature Engineering - Domain Specific
Feature Engineering - Interaction Features
Course Review
EDA - Engineered features & significance tests
Exploratory Data Analysis Part 2
ANOVA Concept- Intuition
ANOVA Concept - Maths
Significance Tests
Data pre-processing
Label Encoding
Data Preprocessing for Model Building
Feature Encoding Approaches
Course Review
Evaluation methods for regression
Evaluation Metrics
Introduction to time series modeling
Introduction to Time Series Modeling
Time Series and Stationarity Concepts
ACF and PACF
Course Review
Time series model - ARIMA
Introduction to ARIMA Modeling
AR and MA Models - Part 1
AR and MA Models - Part 2
Auto Arima concept
Strategy 1 - ARIMA Forecasting Demo
Strategy 1 - ARIMA Forecasting Demo - Part 2
Durbin Watson Statistic
Strategy 2 - Auto ARIMA
Strategy 3 - AutoARIMA for Genre
Time series model - SARIMA and SARIMAX
SARIMA and SARIMAX
Strategy 4 SARIMA Demo
Strategy 5 SARIMAX Demo
Exogenous Variables Deepdive Part 1 - Time Based and Demographics
Exogenous Variables Deepdive Part 2 - Qualitative and Promotions
Exogenous Variables Deepdive Part 3 - Series decomposition and LifeCycle
Exogenous Variables Deepdive Part 4 - Macro Economic Features
Forecast for Unknown Future
Course Review
Time series model - Prophet by Facebook
Prophet by Facebook
Prophet Forecasting Demo
Machine learning models - XGBoost and CATBoost
New Plan of Attack
XGBoost Demo
CatBoost
CatBoost Demo
Course Review
Model improvement and interpretation
Hyper Parameters and Tuning
Cohorted Ensembles
Cohorted Ensembles Demo
Conclusion
Final Words
Course Review