Udemy – Build an AWS Machine Learning Pipeline for Object Detection 2024-12
Udemy – Build an AWS Machine Learning Pipeline for Object Detection 2024-12 Downloadly IRSpace
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Build an AWS Machine Learning Pipeline for Object Detection, In this course, we will cover all the necessary steps to create a robust and reliable machine learning pipeline, from data preprocessing to hyperparameter tuning for object detection. We will start by introducing you to the basics of AWS Sagemaker, a fully-managed service that provides developers and data scientists with the ability to build, train, and deploy machine learning models quickly and easily. You will learn how to use Sagemaker to preprocess and prepare your data for machine learning, as well as how to build and train your own machine learning models using Sagemaker’s built-in algorithms. Next, we will dive into AWS Step Functions, which allow you to coordinate and manage the different steps of your machine learning pipeline.
You will learn how to create a scalable, secure, and robust machine learning pipeline using Step Functions, and how to use Lambda functions to trigger your pipeline’s different steps. In addition, we will cover deep learning related topics, including how to use neural networks for object detection, and how to use hyperparameter tuning to optimize your machine learning models for different use cases. Finally, we will walk you through the creation of a web application that will interact with your machine learning pipeline. You will learn how to use React, Next.js, Express, and MongoDB to build a web app that will allow users to submit data to your pipeline, view the results, and track the progress of their jobs.
What you’ll learn
- Learn how you can use Google’s Open Images Dataset V7 to use any custom dataset you want
- Create Sagemaker Domains
- Upload and Stream data into you Sagemaker Environment
- Learn how to set up secure IAM roles on AWS
- Build a Production Ready Object detection Algorithm
- Use Pandas, Numpy for Feature and Data Engineering
- Understanding Object detection annotations
- Visualising Images and Bounding Boxes with Matplotlib
- Learn how Sagemaker’s Elastic File System(EFS) works
- Use AWS’ built in Object detection detection algorithm with Transfer Learning
- How to set up Transfer Learning with both VGG-16 and ResNet-50 in AWS
- Learn how to save images to RecordIO format
- Learn what RecordIO format is
- Learn what .lst files are and why we need them with Object Detection in AWS
Who this course is for
- For developers who want to take their machine learning skills to the next lever by being able to not only build machine learning models, but also incorporate them in a complex, secure production ready machine learning pipeline
Specificatoin of Build an AWS Machine Learning Pipeline for Object Detection
- Publisher : Udemy
- Teacher : Patrik Szepesi
- Language : English
- Level : Intermediate
- Number of Course : 139
- Duration : 16 hours and 30 minutes
Content
Requirements
- Laptop with Internet Access
- AWS account
- Knowledge of Python and basic Machine Learning
- Spend 20-50 dollars on AWS if you want to follow along with me. Note that you can still follow along without having to pay any money
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720p
The 2024/12 version has an increase of 2 lessons and 12 minutes in duration compared to the 2023/2 version. Subtitles have also been added.
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File size
4.9 GB
