Computer Vision and NLP with AWS ML and Python Boto3

Description

In this course, you will :

• Discover the fundamentals of natural language processing.
• Discover how to use AWS NLP services such as Comprehend, Transcribe, Translate, Polly, and others.
• Discover how to perform sentiment analysis on a phrase.
• Learn how to translate text into various languages.
• Learn how to use Transcribe and Polly to create voice-enabled applications.
• Learn how to implement text-to-speech and speech-to-text functionality.
• Learn how to create NER (Named entity recognition).
• Learn how to create and apply POS tagging.
• Discover how to use the AWS SDK for Python with the Boto3 library.

Syllabus :

1. Creating Frontend and backend for web application

• Build frontend for ML Application
• Build Backend for ML Application

 

2. Translation ML app

• Add NLP task (translation)

 

3. Sentiment Analysis ML app

• Creating Sentiment Analysis ML app

 

4. POS tagging for NER (Named Entity Recognition) , word classification

• POS tagging ML App

 

5. Named Entity Recognition

• Detect entity

 

6. Transcribe (Speech to Text)

• Uploading audio file to S3 bucket
• Creating Transcribe job
• Understanding ASR output
• Adding transcribe feature into web application

 

7. Polly

• Creating Polly function
• Adding Polly function into main application

 

8. AWS Reokgnition

• Creating the frontend of Keyword Generator App
• Generating keywords using python script
• Creating Upload function

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