Amazon Web Services (AWS)
Machine Learning with AWS
Course Overview
Machine Learning and Artificial Intelligence is considered a game changer. It is the biggest shift of the decade in Machine Learning. The goal of this 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 and machine learning 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.
Course Length
Target Audience
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.
Course Prerequisites
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
Topic List
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 a 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 modeling.
- Extract and analyze common themes through topic modelling with Amazon Comprehend.
- Sample project: Perform topic modeling 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 up market prices for a given stock
Lesson Five: Using Speech with the Chatbot
- Set up Amazon Connect as a personal call center.
- 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