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Machine Learning Deep Learning Model Deployment

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Machine Learning Deep Learning Model Deployment - 
Deploy Machine Learning Model Python Pickle Flask Serverless REST API TensorFlow Serving PyTorch MLOps MLflow
  • New
  • Created by FutureX Skill
  • English
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In this course you will learn how to deploy Machine Learning Models using various techniques.
Course Structure:
Creating a Model
Saving a Model
Exporting the Model to another environment
Creating a REST API and using it locally
Creating a Machine Learning REST API on a Cloud virtual server
Creating a Serverless Machine Learning REST API using Cloud Functions
Deploying TensorFlow and Keras models using TensorFlow Serving
Deploying PyTorch Models
Creating REST API for Pytorch Models
Tracking Model training experiments and deployment with MLfLow
Python basics and Machine Learning model building with Scikit-learn will be covered in this course. TensorFlow and Pytorch model building is not covered so you should have prior knowledge in that. Focus of the course is mainly Model deployment.
Who this course is for:

Machine Learning beginners

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