In this course you will learn how to deploy Machine Learning Models using various techniques.
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
Converting a PyTorch model to TensorFlow format using ONNX
Creating REST API for Pytorch and TensorFlow Models
Deploying tf-idf and text classifier models for Twitter sentiment analysis
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.