Hello Everyone!!

I am delighted to share that I have attended one workshop on the topic “AI on AWS” under the mentorship of Mr. Vimal Daga Sir. The workshop covered the industrial use-cases of the latest technologies like #aws #AI #MachineLearning with their implementation on cloud platform through pre-created models provided by AWS by using python language.

The key learnings from the workshop are :

  • Al/ML resembles a human brain as it also performs tasks as per provided experience/model and creates patterns that give it intelligence which helps it in behaving/working like a human brain.
  • For performing ML-related tasks, we need resources with high computation powers, and to avoid the cost and maintenance of such expensive hardware, we opt for cloud services like AWS.
  • In AWS, Amazon Rekognition provides a wide range of services/models like face recognition, image recognition, voice analysis, face comparison, and many more. These smart services help a lot in the field of AI.
  • Confidence Score is just like an accuracy score which helps in predicting particular labels in images/videos.
  • Amazon Rekognition service can be accessed either through web UI of AWS portal or can be accessed through AWS SDK which is boto3 (a python library).
  • Bounding Box provides coordinates that specify the area of the image that contains specific objects detected.
  • OpenCV helps in contacting webcam with python code.
  • In AWS, IAM service is used for creating users/roles and assigning specific/limited power and permissions to them.
  • Labels in Amazon Rek help us to know/accurately predict all the objects that are present in the uploaded image.
  • In AWS, Amazon Polly is a service that turns text into lifelike speech, allowing you to create applications that talk and build entirely new categories of speech-enabled products.
  • Amazon Lex is a service provided by AWS that helps in building a chatbot using text and voice services.
  • Natural Language Processing or NLP is defined as the automatic manipulation of natural language, like speech and text, by software.
  • In Amazon Lex, intent is an option to tell our requirements like what type of chatbot we want to build.
  • In AWS, Amazon Kendra is a service that helps us to create our own search engine on the provided data either document or pdf.
  • Amazon Kendra helps us by reducing the time taken to search the requirement in the given data.
  • Amazon code guru is a service offered by AWS that helps in reviewing the code created in our local system and also gives suggestions for improvement and guides us about our code like which part of code is consuming more resources.
  • For accessing the profiler of the code guru, first, we have to install codeguru profiler agent in our local system then we have to run the following agent command:
  • python -m codeguru-profiler-agent -p <profiler name> — <region name>
  • Amazon Comprehend service is used to extract useful information from the paragraph.
  • Amazon Textract is a machine learning service that automatically extracts text, handwriting, and data from scanned documents that go beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables.
  • Amazon Translate is a service of AWS to translate text from one language to another language.
  • Amazon Personalize is the service of AWS that makes the developers add individualized recommendations to the client to their applications
  • Amazon Fraud Detector is an AWS service that helps in detecting frauds with the help of logs and data we provide to it.

In the end, I would like to thank Vimal Sir and Preeti Ma’am for always supporting us and for conducting such an amazing workshop of so much in-depth knowledge and practical implementation of the latest technologies.

I am so proud of myself for being a student of Vimal Sir and a part of LinuxWorld.


#AIonAWSbyLW #AIbyLW #AWSbyLW #AIworkshop #AIwithAWS #AWSworkshop #RightEducation #vimaldaga #makingindiafutureready



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