Machine Learning Tools and Services

1. Define three layers of the ML stack.

2. Identify common ML tools and frameworks.

3. Describe different ASW ML services.

4. Explain Amazon SageMaker and its key features.

Machine Learning Stacks

1. A stack is a collection of resources that you can manage as a single unit. Thus, you can create, update, or delete a collection of resources by creating, updating, and deleting stacks.

2. Types:

   • The data layer: where the data that will feed into the ML model is stored.

   • The model layer: contains the model and algorithms that build predictions, based on data that the model collects.

   • The deployment and monitoring layer: The model is working in a live environment and producing ML tasks.

Tools for ML

1. Jupyter Notebook

2. Jupyter Lab

3. Pandas

4. Matplotlib

5. Seaborn

6. Numpy

7. Scikit-learn

Framework

1. Customized scripting.

2. Community of developers.

3. Integration with AWS.

AWS Instance Designed for ML Applications

1. Amazon EC2 C5 and C5n instances:

   • Deliver cost-effective high performance at a low price per compute ratio for running advanced compute-intensive workloads.

   • Ex: Scientific modeling, distributed analytics, and ML or DL inference.

2. Amazon EC2 P3 instances: 

   • Offer P3 family: data scientists, researchers, and developers.

   • Be ideal for ML workloads that need massive parallel processing power.

3. AWS IoT Greengrass:

   • Bring intelligence to edge devices.

   • Provide infrastructure for building machine learning for IoT devices.

4. Amazon Elastic Inference:

   • Attach low-cost GPU-powered acceleration to Amazon EC2 and SageMaker.

ML Managed Services Categories

1. Computer Vision:

   • Amazon Rekognition, Amazon Textract.

2. Chatbots:

   • Amazon Lex.

3. Speech:

   • Amazon Polly, Amazon Transcribe.

4. Forecasting:

   • Amazon Forecast.

5. Language:

   • Amazon Comprehend, Amazon Translate.

6. Recommendations:

   • Amazon Personalize.

Amazon Code Whisperer?

1. AI-powered code generators for IDEs and code editors.

2. AI coding companion.

3. AI security scanner.

SageMaker

1. Notebook

2. Instace Types

3. Data Visualization

4. Model Selection

5. Deployment.

6. Marketplace Integration.