AWS Machine Learning

• NEW in 2023 - AWS Generative AI tools / blog announcement(Amazon Bedrock and more) - link
• This repo is a companion to my course on LinkedIn Learning - AWS Machine Learning Essentials - link
• reInvent 2020 ML keynote recap - https://aws.amazon.com/blogs/aws/reinvent-2020-liveblog-machine-learning-keynote/

AWS Machine Learning Service Choices

Chart below for reference, grouped by category -- SaaS, PaaS and IaaS for AWS Machine Learning services.

Learn more

Core Machine Learning Concepts

• LEARN via an open source course homemade-machine-learning - use Jupyter notebook examples which explain & demo key ML algorithms in Python - link
• LEARN using the open source sci-kit learn Python library - link

Learn Convolutional Neural Network Concepts (CNNs)

• SEE fashion mnist and get sample data - link
• TRY CNN example with TensorFlow/Keras and with mnist data - link
• LEARN CNN example with fashion mnist data - link
• LEARN CNN encoding for mnist - link
• LEARN theoretic and advanced TensorFlow ML concepts - link

12 Hour Data Science Course

Work with many example Jupyter (SageMaker) notebooks in this companion repo which includes a large number of example notebooks for data science (machine learning) use cases. This Repo is a companion to the book "Data Science on AWS"

• Here's the link to this repo w/the example notebooks

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AWS Machine Learning Resources

• READ main AWS ML blog at https://aws.amazon.com/blogs/machine-learning/
• WORK with training from AWS ML Team at https://aws.amazon.com/machine-learning/mlu/
  • NLP, Tabular Data or Computer Vision scenarios
• PRACTICE using any of of a large number of AWS SageMaker Jupyter notebook examples
  • create a AWS SageMaker Notebook instance
  • connect to Jupyter
  • navigate to the SageMaker Examples tab your SageMaker notebook instance
  • The URL will look something like this - https://demo.notebook.us-east-1.sagemaker.aws/tree#examples
  • Shown below is a screenshot of example notebook categories available

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