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0:00 Introduction
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Classroom Contents
Building Realtime End-to-End Sales Forecasting ML Pipeline
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- 1 0:00 Introduction
- 2 2:19 System Architecture Overview
- 3 5:34 MLOps Architecture
- 4 8:24 Data Flow, Deployment, ML Pipeline and Inference Architecture
- 5 15:49 Component Interaction Process Flow
- 6 27:35 Getting Started with Astro
- 7 31:55 Environment and Project Setup
- 8 37:27 Adding More Services to Astro
- 9 51:21 Sales Forecast Model Training
- 10 1:01:22 Advanced Realistic Sales Data Extraction
- 11 2:01:53 Sales, Promotion and Traffic Data Validation
- 12 2:19:32 End to End ML Models Training
- 13 4:14:30 ML Models Evaluation, Model Registration and Production Deployment
- 14 4:37:15 End to End Pipeline Testing and Validation
- 15 4:40:10 Pipeline Results and Validation
- 16 4:44:00 Streamlit UI Deployment and Realtime Inference
- 17 4:58:00 Outro
