Udemy – Deploy a Production Machine Learning model with AWS & React 2024-12

Udemy – Deploy a Production Machine Learning model with AWS & React 2024-12 Downloadly IRSpace

Aug 16, 2025 - 06:56 Updated: Aug 17, 2025 - 19:31

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Udemy – Deploy a Production Machine Learning model with AWS & React 2024-12

Deploy a Production Machine Learning model with AWS & React, In this course we are going to use AWS Sagemaker, AWS API Gateway, Lambda, React.js, Node.js, Express.js MongoDB and DigitalOcean to create a secure, scalable, and robust production ready enterprise level image classifier. We will be using best practices and setting up IAM policies to first create a secure environment in AWS. Then we will be using AWS’ built in SageMaker Studio Notebooks where I am going to show you guys how you can use any custom dataset you want. We will perfrom Exploratory data analysis on our dataset with Matplotlib, Seaborn, Pandas and Numpy.

After getting insightful information about dataset we will set up our Hyperparameter Tuning Job in AWS where I will show you guys how to use GPU instances to speed up training and I will even show you guys how to use multi GPU instance training. We will then evaluate our training jobs, and look at some metrics such as Precision, Recall and F1 Score. Upon evaluation we will deploy our deep learning model on AWS with the help of AWS API Gateway and Lambda functions. We will then test our API with Postman, and see if we get inference results. After that is completed we will secure our endpoints and set up autoscaling to prevent latency issues. Finally we will build our web application which will have access to the AWS API. After that we will deploy our web application to DigitalOcean.

What you’ll learn

Deploy a production ready robust, scalable, secure Machine Learning application
Set up Hyperparameter Tuning in AWS
Find the best Hyperparameters with Bayesian search
Use Matplotlib, Numpy, Pandas, Seaborn in SageMaker
Use AutoScaling for our deployed Endpoints in AWS
Use multi-instance GPU instance for training in AWS
Learn how to use SageMaker Notebooks for any Machine Learning task in AWS
Set up AWS API Gateway to deploy our model to the internet
Secure AWS Endpoints with limited IP address access
Use any custom dataset for training
Set up IAM policies in AWS
Set up Lambda concurrency in AWS
Data Visualization in SageMaker
Learn how to do MLOps in AWS

Who this course is for

Those with some ML experience who are hoping to take their skills to the next step by being able to deploy their deep learning models to production

Specificatoin of Deploy a Production Machine Learning model with AWS & React

Publisher : Udemy
Teacher : Patrik Szepesi
Language : English
Level : All Levels
Number of Course : 74
Duration : 5 hours and 56 minutes

Content of Deploy a Production Machine Learning model with AWS & React

Deploy a Production Machine Learning model with AWS & React

Requirements

Any laptop and an internet connection
Some Python and Machine Learning Knowledge
about 15-40 dollars for using AWS resources(Optional, only applies if you follow along with me)