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FreeMLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment
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The project builds a YouTube viewer sentiment analyzer and wraps it in a Chrome extension. Along the way it improves a baseline with TF-IDF and handling of imbalanced data, sets up MLflow on AWS for tracking, and structures the work as a DVC pipeline with components for ingestion, preprocessing, training, evaluation and registration.
Beginners who want to see a full project, from a first model through a Flask API and browser plugin to Docker and CI/CD on AWS. It is strongest for learners who would rather build along than read about each stage.
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: https://www.youtube.com/@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 learning: https://scrimba.com/freecodecamp
⭐️ 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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Learn to code for free and get a developer job: https://www.freecodecamp.org
Read hundreds of articles on programming: https://freecodecamp.org/news
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