Self Reflection of AI on AWS workshop

Following are the concepts that I have learnt through this workshop:-

🎯 AI/ML resemble to human brain as it performs task as human brain it take input via eyes(visual) , mouth and ears (voice) and also take input from the sensors like fingerprint , microphone , camera and read the object

🎯 Amazon recognition service provide the images or videos related stuffs and help in interpreting images with various functionalities without actually training a model by ourselves

🎯 Confidence Score can also be called as the accuracy of the model’s prediction

🎯 Boto3 library of Python helps in Communicating with the AWS APIs of the services

🎯 AWS Rekognition returns the data of bounding boxes for the images after processing them

🎯 "opencv-python” library helps in connecting the camera with python

🎯 We need cloud-based services for ml-based projects because ML-based projects can take many hours or days to get trained which again might cost time and money

🎯 Amazon Lex is the Amazon service for building your own customized Chatbot which enables us to build applications using a speech or text interface

🎯 NLP is Natural language processing that makes it possible for computers to read text, hear speech, interpret it, measure sentiment, and determine which parts are important

🎯 Intent is a function in Amazon Lex Service that helps us to provide the functionality to our chatbot

🎯 Amazon Kendra is an AWS service that relies on machine learning to search data stored in multiple sources

🎯 Amazon Textract is a cloud-based service which is also called a machine learning service that automatically extracts text, handwriting, and data from scanned documents

🎯 Amazon Fraud Detector is a cloud-based service used to create an additional layer of security for our application that helps us to fight auto bots and other fraud done by hackers

🎯 Amazon Comprehend gives the facility to analyse the text and extract some data, like name, noun,

🎯 Amazon Personalize is used to personalize the experience used for creating a recommendation engine for your application   

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