This comprehensive course teaches you to build an end-to-end MLOps pipeline that analyzes YouTube sentiment in real-time through a Chrome extension. You'll master modern ML tools like MLflow, DVC, Docker, and AWS while developing a complete solution from data collection to deployment. You'll gain hands-on experience with real-world ML engineering and MLOps practices.
Code:
Bappy's YouTube Channel:
Bappy's LinkedIn profile:
Bappy's Udemy:
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning:
⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction & Project Planning
⌨️ (0:19:52) Data Collection
⌨️ (0:21:28) Data Preprocessing & EDA
⌨️ (0:41:43) Setup MLFlow Server on AWS
⌨️ (0:57:34) Building Baseline Model
⌨️ (1:06:25) Improving Baseline Model - BOW, TFIDF
⌨️ (1:14:56) Improving Baseline Model - Max features
⌨️ (1:20:55) Improving Baseline Model - Handling Imbalanced Data
⌨️ (1:26:54) Improving Baseline Model - Hyperparameter tuning with Multiple Improving Baseline Model
⌨️ (1:32:13) Stacking Models
⌨️ (1:34:14) Building an ML Pipeline using DVC
⌨️ (1:38:22) Data Ingestion Component
⌨️ (1:46:01) Data Preprocessing Component
⌨️ (1:48:11) Model Building Component
⌨️ (1:52:28) Model Evaluation Component with MLFlow
⌨️ (1:59:58) Model Register Component with MLFlow
⌨️ (2:02:42) Flask API Implementation
⌨️ (2:14:20) Implementation of Chrome Plugin
⌨️ (2:24:27) Adding Docker
⌨️ (2:25:46) CICD Deployment on AWS
🎉 Thanks
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2025/06/13
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