Machine Learning Deep Learning model deployment | Data Science Online Course by Udemy

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Serving TensorFlow Keras PyTorch Python model Flask Serverless REST API MLOps MLflow Cloud GCP NLP tensorflow. js deploy

An excellent training about Data Science

Machine Learning Deep Learning model deployment

In this course you will learn how to deploy Machine Learning Models using various techniques. Course Structure: Creating a ModelSaving a ModelExporting the Model to another environmentCreating a REST API and using it locallyCreating a Machine Learning REST API on a Cloud virtual serverCreating a Serverless Machine Learning REST API using Cloud FunctionsDeploying TensorFlow and Keras models using TensorFlow ServingDeploying PyTorch ModelsConverting a PyTorch model to TensorFlow format using ONNXCreating REST API for Pytorch and TensorFlow ModelsDeploying tf-idf and text classifier models for Twitter sentiment analysisDeploying models using TensorFlow. js and JavaScriptTracking Model training experiments and deployment with MLfLowPython 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.

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