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Data Science in Production: Building Scalable Model Pipelines
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1.
Introduction to Building Scalable Model Pipelines
Course Overview
Applied Data Science
Python for Scalable Compute
Cloud Environments
Coding Environments
Quiz - Data Science Preliminary Concepts
🛑 Important Note!
Introduction to Datasets
- BigQuery to Pandas
- Kaggle to Pandas
Quiz - Importing Datasets
Prototype Models
- Linear Regression
- Logistic Regression
- Keras Regression
Automated Feature Engineering
Quiz - Prototype Modeling
Conclusion : Data science models, tools and environments
2.
Models as Web Endpoints
Introduction to Models as Web Endpoints
Web Services
Echo Service
Model Persistence
Model Endpoints
Quiz - Web Services and Persistent Models
Deploying a Web Endpoint
- Gunicorn
- Heroku
Interactive Web Services with Dash
Quiz - Web Deployments
Conclusion : Models as Web Endpoints
3.
Models as Serverless Functions
Introduction to Models as Serverless Functions
Managed Services
Cloud Functions (GCP)
- Echo Service
- Cloud Storage (GCS)
- Model Function
- Keras Model
- Access Control
- Model Refreshes
Quiz - Managed Services
Lambda Functions (AWS)
- Echo Function
- Simple Storage Service (S3)
- Model Function
- API Gateway
Quiz - Lambda Functions
Conclusion
Cloud Lab
Premium Plus
Create an Echo Function in Lambda
Cloud Lab
Premium Plus
Working with S3 in Lambda
Cloud Lab
Premium Plus
Working with API in Lambda
4.
Containers for Reproducible Models
Introduction to Containers as Reproducible Models
Docker
Orchestration
- AWS Container Registry (ECR)
- AWS Container Service (ECS)
- Load Balancing
Kubernetes on GCP
Quiz - Containers
Conclusion: Containers as Reproducible Models
Cloud Lab
Premium Plus
Working with AWS Container Registry
5.
Workflow Tools for Model Pipelines
Introduction to Workflow Tools for Model Pipelines
Sklearn Workflow
Cron
- Cloud Cron
Quiz - Workflows and Scheduling
Workflow Tools
- Apache Airflow
- Managed Airflow
Quiz - Workflow Tools
Conclusion : Workflow Tools for Model Pipelines
6.
PySpark for Batch Pipelines
Introduction to PySpark for Batch Pipelines
Spark Environments
- Spark Clusters
- Databricks Community Edition
Staging Data
Quiz - Spark Environments
A PySpark Primer
- Persisting Dataframes
- Converting Dataframes
- Transforming Data
- Pandas UDFs
- Best Practices
Quiz - PySpark
MLlib Batch Pipeline
- Model Application
Distributed Deep Learning
Distributed Feature Engineering
Quiz - Machine Learning in PySpark
GCP Model Pipeline
- BigQuery Export
- GCP Credentials
- Model Pipeline
Productizing PySpark
Quiz - GCP Model Pipeline
Conclusion : Working tools for model pipelines
7.
Cloud Dataflow for Batch Modeling
Introduction to Cloud Dataflow and Batch Modeling
Apache Beam
Batch Model Pipeline
- Model Training
- BigQuery Publish
- Datastore Publish
Quiz - Dataflow and Batch Modeling
Conclusion : Cloud Dataflow for Batch Modeling
8.
Streaming Model Workflows
Introduction to Streaming Model Workflows
Spark Streaming
- Apache Kafka
- Sklearn Streaming 1
- Sklearn Streaming 2
Dataflow Streaming
- PubSub
- Natality Streaming
Quiz - Streaming Model Workflows
Conclusion : Streaming model workflows
9.
Course Conclusion
Thank You
Data Science in Production: Building Scalable Model Pipelines
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Quiz - PySpark
Quiz - PySpark
A comprehensive quiz on PySpark.
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