Machine Learning Deep Learning Model Deployment

 

Machine Learning Deep Learning Model Deployment

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Machine Learning Deep Learning Model Deployment Deploy Model Python Pickle Flask Serverless REST API TensorFlow Serving Keras PyTorch MLOps MLflow Cloud GCP New

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Current priceRp149,000
Original PriceRp279,000
Discount47% off

What you'll learn

• Machine Learning Deep Learning Model Deployment techniques
• Simple Model building with Scikit-Learn , TensorFlow and PyTorch
• Deploying Machine Learning Models on cloud instances
• TensorFlow Serving and extracting weights from PyTorch Models
• Creating Serverless REST API for Machine Learning models
• Machine Learning experiment and deployment using MLflow

Requirements

• Prior Machine Learning and Deep Learning background required but not a must have as we are covering Model building process also

Description

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. You will also learn how to build and deploy a Neural Network using TensorFlow Keras and PyTorch. Google Cloud (GCP) free trial account is required to try out some of the labs designed for cloud environment.