Examples

The following are some example use cases of DFFML.

Contents:

• Notebooks
  • Moving Between Models
  • Evaluating Model Performance
  • Tuning Models
  • Saving and loading models
  • Ensemble by stacking
  • Transfer Learning
  • Working with Multi-Output models
• Automating Classification
  • CGI Application
  • Setup
  • Gathering Data
  • Training our Model
  • Making a Prediction
  • Modifying the Legacy App
• Meta Static Analysis
  • Tools
  • Plan
  • Creating our Package
  • Installing Static Analysis Tools
  • Safety Operation
  • Bandit Operation
  • What’s the Data Flow?
  • PyPi Operations
  • CLI
  • Visualizing the DataFlow
  • Registering Operations
• DataFlow HTTP Deployment
  • Config Files
  • MultiComms
  • HTTP Channel Config
  • Serving the DataFlow
  • Combining Operations
  • Redeploying
• InnerSource
  • InnerSource Portal
  • InnerSource Microservice
• MNIST Handwriten Digits
• Flower17 Species Classification
  • Using OpenCV to extract features and then training on a Scikit-Learn model
  • The Transfer Learning approach with Convolution Neural Networks
• COVID Forecasting
  • Plan
  • Setup
  • Code
• Continuous Deployment of DataFlows
  • Deploying with the HTTP Service
  • Deploying via container
  • Redeploying on receiving GitHub webhook
• Ice Cream Sales
  • Dataset
  • Operations
  • Dataflow
  • Merge Command
  • Model Install
  • Model Training
  • Model Accuracy
  • Prediction
• Data Cleanup
  • Data Cleanup Operations
  • Data Cleanup Operations