Lecture 21: Bias vs Variance In Machine Learning

Lecture 22: Ensemble Learning – Bagging

Lecture 23: Introduction (Real Estate Price Prediction Project)

Lecture 24: Data Cleaning (Real Estate Price Prediction Project)

Lecture 25: Feature Engineering (Real Estate Price Prediction)

Lecture 26: Outlier Removal (Real Estate Price Prediction Project)

Lecture 27: Model Building (Real Estate Price Prediction Project)

Lecture 28: Python Flask Server (Real Estate Price Prediction)

Lecture 29: Website or UI (Real Estate Price Prediction Project)

Lecture 30: Deploy machine learning model to production AWS (Amazon EC2 instance)

Lecture 31: Part 1 Introduction | Image Classification

Lecture 32: Part 2 Data Collection | Image Classification

Lecture 33: Part 3 Data Cleaning | Image Classification

Lecture 35: Part 5 Training a Model | Image Classification

Lecture 36: Part 6 Flask Server | Image Classification

Lecture 37: Part 7 Build Website | Image Classification

Lecture 38: Part 8 Deployment & Exercise | Image Classification

Lecture 39: What is feature engineering

Lecture 40: Outlier detection and removal using percentile