Learn AWS with Python Boto3- Hands On

Build a Flask frontend for a machine learning app by installing Flask, defining routes, and rendering html; use natural language processing for translation, sentiment, and part of speech tagging.

Build a Flask backend for an ml app that collects user input and language, translates text, and renders nlp results including spam detection, sentiment analysis, and named entity recognition.

Implement a translate function in a Python app, install dependencies in a virtual environment, configure an access token, and test translating English to a user-selected language (Spanish) with JSON output.

Build a web translation app using AWS translate with Python, calling the translation function to convert input text into a chosen language and display the result.

Create a sentiment analysis app using AWS Comprehend with Python boto3 to classify text as positive, negative, or neutral for product reviews and marketing insights.

Build a sentiment analysis ml app on AWS with Python boto3 that uses AWS Comprehend to classify text into sentiment categories and map scores for a practical review analysis demo.

Explore building a pos tagging ml app that classifies words by part of speech, outputs json, and demonstrates named entity recognition and disambiguation for chatbot nlp tasks.

Learn to recognize named entities in text using a Python detect entities function, identifying person, location, organization, time, and other types, and extract results for a web application.

Learn to convert audio or video speech into text using Amazon Transcribe, create an index for easy search, and upload files to an S3 bucket with a transcription workflow.

Learn to create a transcription job with AWS Transcribe using Python and boto3, handling input audio in S3, configuring language code and job name, and monitoring progress.

Learn how to start an AWS Transcribe job with Python boto3, monitor its status, and retrieve a json transcript with language code and word-level timestamps, and view its output URL.

Add a transcribe feature to a Python web app by extracting the transcript string from a JSON output with a dedicated function.

Demonstrate building a transcribe ML app using AWS and Python Boto3 through hands-on steps for practical transcription workflows.

Learn how to use boto3 to upload, download, and manage files in an AWS S3 bucket, including authenticating with access keys, and performing put, get, and delete operations.

Learn to configure AWS EC2 permissions in the console, enable full access, and use a Python package to create and describe EC2 instances, outlining the basic steps.

Create and manage aws iam users with boto3 by provisioning new users, generating access keys, listing users, updating names, and deleting users to demonstrate identity management.

Learn to use Amazon Comprehend to detect entities in text and extract details. Configure permissions and policies for Amazon Comprehend, and implement hands-on entity extraction workflows using AWS.

Learn how to use Amazon Comprehend to detect key phrases in text with a Python script, and observe how the extracted phrases compare to the full text.

Explore Amazon Comprehend to detect sentiment, extract key phrases, and analyze syntax from text for practical analysis.

Learn to build a Python boto3 powered Amazon Polly app, install dependencies, and synthesize speech from text using different voices (female and male) with a simple script.

Learn to use AWS Rekognition with Python Boto3 to detect labels, objects, scenes, and text in images. Build hands-on skills by analyzing images and extracting label data and text scores.

Explore how AWS Rekognition detects faces and performs facial analysis, including facial landmarks, using Python and boto3 for hands-on image understanding.

Explore how AWS Rekognition celebrity recognition analyzes an image to identify and compare celebrities, retrieve biographical details, and infer occupations like actor or producer.

Perform face comparison between two images using AWS Rekognition, evaluate match confidence, and determine whether the faces belong to the same person.

Learn how AWS Rekognition extracts text from images using the text in image feature, capturing lines and positions to support OCR workflows.

Learn to use AWS Translate with Python Boto3 to translate text from English to German, including handling language codes and a hands-on command prompt demonstration.

Learn to create an AWS Transcribe job with a Python script, configure permissions, run the transcription, and obtain a time-stamped JSON transcript from audio.

Learn to configure AWS Kinesis permissions, create and describe streams, and write records with partition keys and shards in a hands-on workflow.