Machine Learning Deep Learning Model Deployment

1.5 hours




Deploy Machine Learning Model Python Pickle Flask Serverless REST API TensorFlow Serving PyTorch MLOps MLflow


In this course you will learn how to deploy Machine Learning Models using various techniques. You should have basic understanding of Python and Machine Learning before starting on this course.

Course Structure:

  1. Creating a Model
  2. Saving a Model
  3. Exporting the Model to another environment
  4. Creating a REST API and using it locally
  5. Creating a Machine Learning REST API on a Cloud virtual server
  6. Creating a Serverless Machine Learning REST API using Cloud Functions
  7. Deploying TensorFlow and Keras models using TensorFlow Serving
  8. Deploying PyTorch Models
  9. Creating REST API for Pytorch Models
  10. Tracking Model training experiments and deployment with MLfLow


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