Course curriculum

  • 1
    Introduction to the Course
    • Introduction: Project Planning
  • 2
    Data Management & Preprocessing
    • Data Collection
    • Data Preprocessing (EDA)
    • Setup MLFlow Server on AWS
  • 3
    Building Baseline Model with MLflow (MLOps)
    • Building Baseline Model
    • Improving Baseline Model - BOW_ TFIDF
    • Improving Baseline Model - Max features
    • Improving Baseline Model - Handling Imbalanced
    • Hyperparameter tuning with Mutiple Model
    • Improving Baseline Model - Stacking Models
  • 4
    Building End to End Pipeline using DVC (MLOps)
    • Building ML Pipeline using DVC
    • Data Ingestion Component
    • Data Preprocessing Component
    • Model Building Component
    • Model Evaluation Component
    • Model Register Componen
  • 5
    Implementation Complete Google Chrome Plugin
    • Flask API Implementation
    • Implementation of Chrome Plugin
  • 6
    CICD Deployment on AWS (MLOps)
    • Dockerization
    • AWS CICD Deployment with Github Action