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6 Easy steps to deploy Machine Learning (ML) models in AWS EC2 Instance

6 Easy steps to deploy Machine Learning (ML) models in AWS EC2 Instance

In this tutorial you will learn how to deploy a Machine Learning Application based out of Flask in AWS EC2 Instance.

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Software's required:
WinSCP: https://winscp.net/eng/download.php
PuTTy: https://www.putty.org/

Learn about Flask: https://www.youtube.com/watch?v=MAu1fPqlivk

Learn about Heroku Deployment: https://www.youtube.com/watch?v=mS8N0eKOD3k

Learn about GCP Deployment: https://www.youtube.com/watch?v=JCD8hnc25eU

Learn about Azure Deployment: https://www.youtube.com/watch?v=7eIWF4_FucA

Few GitHub links:

AWS: https://github.com/pik1989/BreastCancerPred_AWS/

Flask: https://github.com/beingdatum/BreastCancerPrediction (Flask)

Heroku+GCP: https://github.com/pik1989/BreastCancerPrediction_Heroku/ (Same Flask code used for Heroku, and almost the same code deployed on Google Cloud Platform)

Azure: https://github.com/pik1989/BreastCancerPrediction_Azure

Video Editing: Poonam Shenoy (https://www.linkedin.com/in/kpoonamshenoy/)

Interested in a 1-1 guidance?
Connect with me!! :

Facebook: https://www.facebook.com/pik.newbie

LinkedIn: https://www.linkedin.com/in/satyajit-pattnaik-b41392102/

Tags Used

machine learning
amazon web services
cloud computing
aws deployment
aws satyajit
data science
deploy ml models
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machine learning models cloud
aws cloud practitioner
aws sagemaker
aws s3
aws machine learning certification
aws ec2
ec2 deployment
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aws ec2 machine learning
satyajit pattnaik
cloud models
deploy end to end
ml projects
data science projects
public cloud
private cloud
software defined networking

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8 сентября 2020 г. 21:19:23
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