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⌨️ 0:19:52 Data Collection
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Classroom Contents
MLOps Pipeline with Python, AWS, Docker - YouTube Viewer Sentiment
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- 1 ⌨️ 0:00:00 Introduction & Project Planning
- 2 ⌨️ 0:19:52 Data Collection
- 3 ⌨️ 0:21:28 Data Preprocessing & EDA
- 4 ⌨️ 0:41:43 Setup MLFlow Server on AWS
- 5 ⌨️ 0:57:34 Building Baseline Model
- 6 ⌨️ 1:06:25 Improving Baseline Model - BOW, TFIDF
- 7 ⌨️ 1:14:56 Improving Baseline Model - Max features
- 8 ⌨️ 1:20:55 Improving Baseline Model - Handling Imbalanced Data
- 9 ⌨️ 1:26:54 Improving Baseline Model - Hyperparameter tuning with Multiple Improving Baseline Model
- 10 ⌨️ 1:32:13 Stacking Models
- 11 ⌨️ 1:34:14 Building an ML Pipeline using DVC
- 12 ⌨️ 1:38:22 Data Ingestion Component
- 13 ⌨️ 1:46:01 Data Preprocessing Component
- 14 ⌨️ 1:48:11 Model Building Component
- 15 ⌨️ 1:52:28 Model Evaluation Component with MLFlow
- 16 ⌨️ 1:59:58 Model Register Component with MLFlow
- 17 ⌨️ 2:02:42 Flask API Implementation
- 18 ⌨️ 2:14:20 Implementation of Chrome Plugin
- 19 ⌨️ 2:24:27 Adding Docker
- 20 ⌨️ 2:25:46 CICD Deployment on AWS
