Dive into a comprehensive 2.5-hour video course on AWS Rekognition using Python. Learn to harness the power of Amazon's image and video analysis service, from creating your first machine learning model to implementing face detection. Explore key concepts like uploading datasets to S3 buckets, creating training data sources, and generating real-time predictions. Master practical skills using PyCharm IDE, Python Boto3, and AWS Rekognition API. Gain insights into AI vs ML, AWS pricing, and service limitations. Perfect for developers looking to integrate advanced image analysis capabilities into their applications using AWS Rekognition and Python.
Overview
Syllabus
Course Introduction.
Course pre-requisites.
Create your first AWS machine learning model.
Machine learning project cleanup.
Review and feedback.
Uploading ML dataset to AWS S3 Bucket.
Creating training data source and ML model.
Creating predictions in real time.
AWS billing alerts .
Difference between Artificial Intelligence and Machine Learning.
AWS Machine Learning pricing.
How to download and install PyCharm IDE.
Programmatic access to AWS user.
Python Boto 3.
Creating an image directory in PyCharm.
How to upload images to Web Server.
Python PPRINT module.
Creating Python helper file.
Fetching images from Web Server using Python.
Extracting label names.
Face detection using Python.
Fetching images from AWS S3 Bucket using Python code.
AWS Rekognition limitations.
Taught by
ClayDeskE-Learning
