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MLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment Analytics Table

Income Estimates for MLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment

Based on this YouTube video's total view count of 104K views and industry-standard rates, the estimated total earning is $73 - $209 through ad revenue. Historical data is not yet available to calculate daily, weekly, or monthly averages.

About MLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment

Explore MLOps Pipeline with Python, AWS, Docker – YouTube Viewer Sentiment with 104,357 views, 2,726 likes, and 82 comments. Experience the impact of this video content that has captured audience attention.

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 -- 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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