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Скачать или смотреть Building Realtime End to End Sales Forecasting AI from Scratch

  • CodeWithYu
  • 2025-08-21
  • 6044
Building Realtime End to End Sales Forecasting AI from Scratch
data engineeringsales forecastingml pipelineend to end ml pipelineastroastronomerapache airflowairflow ml pipelinemachine learning pipelinesales forecasting projectmlopsdata pipelinereal time inferencestreamlitsales predictionproduction ml pipelineml model deploymentml model trainingpython machine learningastro airflow tutorialdata science projectforecasting salesmlops tutorialscalable ml pipelineai pipelineairflow tutorial
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Описание к видео Building Realtime End to End Sales Forecasting AI from Scratch

In this in-depth, hands-on project, we’ll design, build, and deploy a production-grade Sales Forecasting Machine Learning Pipeline using Astro, the modern data orchestration platform powered by Apache Airflow, the world’s most widely used open-source tool for orchestrating data pipelines.

SIGN UP FOR ASTRO FREE TRIAL - https://astronomer.io/codewithyu

We’ll walk through everything; from system and MLOps architecture to data ingestion, transformation, model training, evaluation, deployment, and real-time inference with a Streamlit UI.

By the end of this video, you’ll have the skills and knowledge to deploy your own scalable, production-ready ML pipeline.

💡 What You’ll Learn:
✅ Designing robust System & MLOps architectures for ML pipelines
✅ Setting up Astro for multi-service orchestration
✅ Ingesting, validating & transforming realistic sales, promotions & traffic data
✅ Training & evaluating advanced forecasting models
✅ Deploying ML models to production with registry integration
✅ Creating a real-time inference UI with Streamlit
✅ Validating and testing end-to-end ML workflows

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

🔗 Resources & Links:
Full Source Code → https://github.com/airscholar/astro-s...
Astro by Astronomer → https://www.astronomer.io/astro
Apache Airflow → https://airflow.apache.org/

💬 Have questions or ideas? Drop them in the comments — I reply to every one!

If this was helpful, LIKE, SUBSCRIBE, and turn on 🔔 notifications so you don’t miss future projects.

#DataEngineering #MachineLearning #MLOps #ApacheAirflow #Astro #Kafka #Spark #SalesForecasting #RealTimeAnalytics #EndToEndPipeline

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