MLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment
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: https://github.com/entbappy/End-to-end-Youtube-Sentiment
Bappy's YouTube Channel: / @dswithbappy
Bappy's LinkedIn profile: https://www.linkedin.com/in/boktiarahmed73/
Bappy's Udemy: https://www.udemy.com/user/boktiar-ahmed-bappy/
❤ ️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learninghttps://scrimba.com/freecodecampmp
⭐ ️ 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 to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual
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