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Machine Learning with AWS

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Machine Learning with AWS

Enroll Now
Duration
2 Days
Delivery
(Online and onsite)
Price
Price Upon Request
The goal of this Machine Learning with AWS course is to guide you through the emerging world of patterns, techniques, and practices, helping you to understand proven solutions to common problems. In this course, you will learn about the various Artificial Intelligence (AI) and Machine Learning (ML) services available on AWS. Through practical hands-on exercises, you’ll learn how to use these services to generate impressive results. By the end of this course, you will have a basic understanding of how to use a wide range of AWS services in your own projects.   See other courses available

Lesson One: Introduction to Amazon Web Services

  • The basics of working on AWS using S3
  • Importing and exporting data.
  • Using the AWS console and identifying the services available for Machine Learning.
  • Create an S3 bucket and import text data into it.

Lesson Two: Summarize Text Documents using NLP

  • Use Amazon Comprehend to detect the language which a document is written in.
  • Extract information such as entities (persons or places), key phrases (noun phrases indicative of the content), and emotional sentiment from a set of documents.
  • Sample project: Set up a Lambda function to process and analyze the imported text using Comprehend.

Lesson Three: Perform Topic Modelling and Theme Extraction

  • Understand what business use cases to apply the machine learning algorithm (Latent Dirichlet Allocation (LDA)) that is used for topic modelling.
  • Extract and analyze common themes through topic modelling with Amazon Comprehend.
  • Sample project: Perform topic modelling on a set of documents and analyze the results.

Lesson Four: Creating Chatbot with Natural Language

  • Explore the basics of chatbots and chatbot design.
  • Set up with the Amazon Lex service and create a sample chatbot to order flowers.
  • Create a custom chatbot which will look upmarket prices for a given stock

Lesson Five: Using Speech with the Chatbot

  • Set up Amazon Connect as a personal call centre.
  • Integrate the chatbot you built in the previous lesson with Amazon Connect.
  • Interact with the chatbot using voice and speech by calling it.

Lesson Six: Analyzing Images with Computer Vision

  • Use Rekognition service for image analysis using computer vision.
  • Detect objects and scenes in images.
  • Detect the need for content moderation in images.
  • Analyze faces and recognize celebrities in images.
  • Compare faces in different images to see how closely they match.
  • Extract text from images

This course is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services.

Hardware:

  • Processor: Intel Core i5 or equivalent
  • Memory: 4GB RAM
  • Storage: 35GB available space
  • An internet connection
  • A keyboard, mouse, or other pointing devices

 

Software:

  • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit
  • Browser: Google Chrome, Latest Version
  • An AWS account
The goal of this Machine Learning with AWS course is to guide you through the emerging world of patterns, techniques, and practices, helping you to understand proven solutions to common problems. In this course, you will learn about the various Artificial Intelligence (AI) and Machine Learning (ML) services available on AWS. Through practical hands-on exercises, you’ll learn how to use these services to generate impressive results. By the end of this course, you will have a basic understanding of how to use a wide range of AWS services in your own projects.   See other courses available

Lesson One: Introduction to Amazon Web Services

  • The basics of working on AWS using S3
  • Importing and exporting data.
  • Using the AWS console and identifying the services available for Machine Learning.
  • Create an S3 bucket and import text data into it.

Lesson Two: Summarize Text Documents using NLP

  • Use Amazon Comprehend to detect the language which a document is written in.
  • Extract information such as entities (persons or places), key phrases (noun phrases indicative of the content), and emotional sentiment from a set of documents.
  • Sample project: Set up a Lambda function to process and analyze the imported text using Comprehend.

Lesson Three: Perform Topic Modelling and Theme Extraction

  • Understand what business use cases to apply the machine learning algorithm (Latent Dirichlet Allocation (LDA)) that is used for topic modelling.
  • Extract and analyze common themes through topic modelling with Amazon Comprehend.
  • Sample project: Perform topic modelling on a set of documents and analyze the results.

Lesson Four: Creating Chatbot with Natural Language

  • Explore the basics of chatbots and chatbot design.
  • Set up with the Amazon Lex service and create a sample chatbot to order flowers.
  • Create a custom chatbot which will look upmarket prices for a given stock

Lesson Five: Using Speech with the Chatbot

  • Set up Amazon Connect as a personal call centre.
  • Integrate the chatbot you built in the previous lesson with Amazon Connect.
  • Interact with the chatbot using voice and speech by calling it.

Lesson Six: Analyzing Images with Computer Vision

  • Use Rekognition service for image analysis using computer vision.
  • Detect objects and scenes in images.
  • Detect the need for content moderation in images.
  • Analyze faces and recognize celebrities in images.
  • Compare faces in different images to see how closely they match.
  • Extract text from images

This course is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services.

Hardware:

  • Processor: Intel Core i5 or equivalent
  • Memory: 4GB RAM
  • Storage: 35GB available space
  • An internet connection
  • A keyboard, mouse, or other pointing devices

 

Software:

  • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit
  • Browser: Google Chrome, Latest Version
  • An AWS account
    Upcoming Dates
  • ` Feb 6 - Feb 7, 2023
  • ` Mar 6 - Mar 7, 2023
  • ` Apr 3 - Apr 4, 2023
  • ` May 1 - May 2, 2023
  • ` May 29 - May 30, 2023
  • ` Jun 26 - Jun 27, 2023