This course on AWS Rekognition using Python aims to teach learners how to incorporate image and video analysis into their applications effortlessly. By utilizing Amazon Rekognition, participants will be able to identify objects, people, text, scenes, and activities in images and videos, as well as detect inappropriate content. The course covers facial analysis, facial search capabilities, and face detection using Python. Students will learn to create AWS machine learning models, upload datasets to AWS S3 Bucket, and make real-time predictions. The teaching method includes video lectures and practical demonstrations. This course is designed for individuals interested in integrating image and video analysis functionalities 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
