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Applied Machine Learning and High-Performance Computing on AWS

You're reading from   Applied Machine Learning and High-Performance Computing on AWS Accelerate the development of machine learning applications following architectural best practices

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803237015
Length 382 pages
Edition 1st Edition
Tools
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Authors (4):
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Trenton Potgieter Trenton Potgieter
Author Profile Icon Trenton Potgieter
Trenton Potgieter
Shreyas Subramanian Shreyas Subramanian
Author Profile Icon Shreyas Subramanian
Shreyas Subramanian
Farooq Sabir Farooq Sabir
Author Profile Icon Farooq Sabir
Farooq Sabir
Mani Khanuja Mani Khanuja
Author Profile Icon Mani Khanuja
Mani Khanuja
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1: Introducing High-Performance Computing
2. Chapter 1: High-Performance Computing Fundamentals FREE CHAPTER 3. Chapter 2: Data Management and Transfer 4. Chapter 3: Compute and Networking 5. Chapter 4: Data Storage 6. Part 2: Applied Modeling
7. Chapter 5: Data Analysis 8. Chapter 6: Distributed Training of Machine Learning Models 9. Chapter 7: Deploying Machine Learning Models at Scale 10. Chapter 8: Optimizing and Managing Machine Learning Models for Edge Deployment 11. Chapter 9: Performance Optimization for Real-Time Inference 12. Chapter 10: Data Visualization 13. Part 3: Driving Innovation Across Industries
14. Chapter 11: Computational Fluid Dynamics 15. Chapter 12: Genomics 16. Chapter 13: Autonomous Vehicles 17. Chapter 14: Numerical Optimization 18. Index 19. Other Books You May Enjoy

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “The next step is to use the model object’s deploy() method to create an HTTPS endpoint.”

A block of code is set as follows:

import numpy as np
import json
with open("horse_cart.jpg", "rb") as f:
    payload = f.read()
    payload = bytearray(payload)

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

smp_options = {
    "enabled":True,
    "parameters": {
        "partitions": 1,
        "placement_strategy": "spread",
        "pipeline": "interleaved",
        "optimize": "speed",
        "ddp": True,
    }
}

Any command-line input or output is written as follows:

$ sudo tail –f /greengrass/v2/logs/com.greengrass.SageMakerEdgeManager.ImageClassification.log

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “On the Configure components page, select the aws.greengrass.SageMakerEdgeManager component, and choose Configure component.”

Tips or important notes

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