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Title: Managed Machine Learning Systems and Internet of Things
Description: Learn the building blocks of Managed ML and Hardware AI with Python
Course Dates:
-
Day 1 (About 3 Hours): Hardware AI & Cloud-Native AI Platforms
- Part A: Chips
- Part B: Cloud-Native Hardware AI Platforms
- Part C: Edge Machine Learning
- Part D: TensorFlow Russian Dolls
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Day 2 (About 3 Hours): Managed ML & AutoML
- Part D: Managed ML & AutoML Overview
- Part E: AWS Managed ML & AutoML
- Part F: GCP Managed ML & AutoML
- Part G: Azure Managed ML & AutoML
You can also download notebooks here: https://github.com/noahgift/managed_ml_systems_and_iot/tree/master/notebooks
- Forbes: How Vertically Integrated AI Stacks Will Affect IT Organizations
- Forbes: Cloud Native Machine Learning and AI
- Forbes: Why There will Be No Data Science Job Titles in 2029
The text content of notebooks is released under the CC-BY-NC-ND license
His most recent books are:
- Pragmatic A.I.: An introduction to Cloud-Based Machine Learning (Pearson, 2018)
- Python for DevOps (O'Reilly, 2020).
His most recent video courses are:
- Essential Machine Learning and A.I. with Python and Jupyter Notebook LiveLessons (Pearson, 2018)
- AWS Certified Machine Learning-Specialty (ML-S) (Pearson, 2019)
- Python for Data Science Complete Video Course Video Training (Pearson, 2019)
- AWS Certified Big Data - Specialty Complete Video Course and Practice Test Video Training (Pearson, 2019)
- Building A.I. Applications on Google Cloud Platform (Pearson, 2019)
- Pragmatic AI and Machine Learning Core Principles (Pearson, 2019)
- Data Engineering with Python and AWS Lambda (Pearson, 2019)
His most recent online courses are: