Description
Build an AWS Machine Learning Pipeline for Object Detection, the Build an AWS Machine Learning Pipeline for Object Detection course is published by Udemy Academy. In this course, we’ll cover all the steps necessary to build a robust and reliable machine learning pipeline, from data preprocessing to hyperparameter tuning for object detection. Next, we introduce you to the basics of AWS Sage Maker, a fully managed service that provides developers and data scientists with the ability to quickly and easily build, train, and deploy machine learning models. You will learn how to use Sagemaker to preprocess and prepare your data for machine learning.
Also, how to build and train your own machine learning models using Sagemaker’s built-in algorithms. Next, we’ll talk about 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 the different steps of your pipeline. In addition, we will cover topics related to deep learning, including how to use neural networks for object recognition and how to use hyperparameter tuning to optimize your machine learning models for different use cases.
What you will learn
- You’ll learn how to use the Google Open Image dataset V7 in any custom dataset you want.
- Create Sagemaker Domains
- Uploading and streaming data in the cloud environment
- You will learn how to create secure IAM roles in AWS
- Creating an algorithm for detecting objects ready for production
- Using Pandas, Numpy for features and data engineering
- Understanding object detection annotations
- Visualization of images and color boxes with MATLAB
- You will learn how Elastic File System (EFS) works
- Using AWS in Object Recognition Algorithm with Transfer Learning
- How to set up transfer learning with VGG-16 and ResNet-50 on AWS
- You will learn how to save images in RecordIO format
- You will learn what the RecordIO format is
- You will learn what .lst is and why we need them for object detection in AWS
Who is this course suitable for?
- For developers who want to improve their machine learning skills and be able to build machine learning models, also learn a complex and secure machine learning pipeline.
Course specifications Build an AWS Machine Learning Pipeline for Object Detection
- Publisher: Udemy
- teacher : Patrik Szepesi
- English language
- Education level: Intermediate
- Number of courses: 137
- Training duration: 16 hours and 18 minutes
Head of the course seasons on 2023-3
Course prerequisites
- 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 video
Installation guide
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download link
File(s) password: www.downloadly.ir
Size
6.16 GB
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