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Deploy machine learning models on Google Cloud AI Platform

Deploy machine learning models on Google Cloud AI Platform

For that, you need frameworks and tooling, software and hardware that help you effectively deploy ML models. These can be frameworks like Tensorflow, Pytorch, and Scikit-Learn for training models, programming languages like Python, Java, and Go, and even cloud environments like AWS, GCP, and Azure.

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What you'll learn

  • How to deploy regression and binary classification machine learning models on Google Cloud AI Platform
  • How to send post requests to the deployed model
  • How to train an very accurate neural network to predict sentiment
  • How to deploy the Natural Language Processing Model
  • Some tips when using Google Cloud AI Platform for deployment
  • How to evaluate model health of a deployed model on Google Cloud AI Platform

Description

My Course is meant for anyone who already knows how to build both machine and deep learning models that is interested in deploying them easily on Google Cloud AI Platform. So that they can send the deployed models post requests. Also you must be familiar with Natural Language Processing and some basic cloud concepts. I will explain everything in the videos. But most importantly you do not need to be an expert in python to do this. However this is again intended for those who already know how to build models with scikitlearn and tensorflow. Because these are the frameworks we will be using and selecting for deployment. Be sure when you do it to select the correct frameworks or you will most likely not be able to deploy your model. That I will also explain in these featured videos. But more importantly enjoy your time learning because should be a very smooth course. If you pay attention you will easily pass my quizzes. Again this is intermediate level not advanced or basic. In this video we will be doing predictions not in jupyter lab with the notebook but be sending post requests to the deployed model. You will mostly be sending post requests to classifiers and regressors the majority of the time. Also in this video you will learn how to build an very accurate neural network for predicting sentiment with the IMDB movie reviews dataset. Then you will deploy it. The datasets we will be working with are the malware dataset from kaggle, the car price dataset from kaggle, and the car purchase dataset from kaggle. However feel free to use your own datasets since you know how to build models. In fact that is strongly encouraged.

View The Best -- > Google Cloud Platform (GCP) - For Techs

  • Google Cloud Platform offers services for compute, storage, networking, big data, machine learning and the internet of things (IoT), as well as cloud management, security and developer tools.
  • How do GCP customers and Google Cloud Platform divide responsibility for security? Google takes care of the lower parts of the stack, and customers are responsible for the higher parts. Consider a single hierarchy of GCP resources.
  • AI Platform is a suite of services on Google Cloud specifically targeted at building, deploying, and managing machine learning models in the cloud.

Online Course CoupoNED
Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.

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