Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications

Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications
Leveraging Cloud-Based Machine Learning on AWS: Real-World Applications
English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 28m | 157 MB

The cost and efficiency of the cloud puts machine learning and artificial intelligence (AI) within the grasp of enterprises big and small. Help your organization tap into their power with Amazon Web Services. This course is a practical approach to leveraging AWS for AI-based applications across a variety of industries, including healthcare, finance, law enforcement, manufacturing, and education. Instructor David Linthicum introduces SageMaker, Amazon’s AI platform, and presents a variety of use cases that demonstrate current best practices, tools, and techniques. He shows how to build and train machine learning models with SageMaker, and integrate them into real-world apps. David also dispels some concerns around AI, such as cost and security, by showcasing real AWS solutions.

Topics include:

  • AI basics
  • AI use cases
  • Building, training, and deploying apps with SageMaker
  • Creating test data and training your SageMaker model
  • AI application walk-through
  • AI costs
  • AI security
  • AI governance
Table of Contents

1 Tap into the power of artificial intelligence (AI) with AWS
2 AI on AWS
3 What you should know
4 AI processing
5 Knowledge creation
6 AI applications
7 AI and cloud computing
8 AI and AWS
9 Healthcare
10 Finance
11 Law enforcement
12 Manufacturing
13 Education
14 SageMaker build
15 SageMaker train
16 SageMaker deploy
17 Create a SageMaker notebook
18 Create test data and train the model
19 What’s different
20 Use case
21 Requirement
22 Design
23 Build
24 Train
25 Deploy
26 Performance
27 Cost
28 Operations
29 Security
30 Governance
31 Next steps