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The Deep Learning Architect's Handbook

You're reading from  The Deep Learning Architect's Handbook

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781803243795
Pages 516 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Ee Kin Chin Ee Kin Chin
Profile icon Ee Kin Chin
LinkedIn
Ee Kin Chin is a Senior Deep Learning Engineer at DataRobot. He holds a Bachelor of Engineering (Honours) in Electronics with a major in Telecommunications. Ee Kin is an expert in the field of Deep Learning, Data Science, Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Python, Keras, Pytorch, and related technologies. He has a proven track record of delivering successful projects in these areas and is dedicated to staying up to date with the latest advancements in the field.
See other products by Ee Kin Chin

Table of Contents (25) Chapters

Preface Part 1 – Foundational Methods
Chapter 1: Deep Learning Life Cycle Chapter 2: Designing Deep Learning Architectures Chapter 3: Understanding Convolutional Neural Networks Chapter 4: Understanding Recurrent Neural Networks Chapter 5: Understanding Autoencoders Chapter 6: Understanding Neural Network Transformers Chapter 7: Deep Neural Architecture Search Chapter 8: Exploring Supervised Deep Learning Chapter 9: Exploring Unsupervised Deep Learning Part 2 – Multimodal Model Insights
Chapter 10: Exploring Model Evaluation Methods Chapter 11: Explaining Neural Network Predictions Chapter 12: Interpreting Neural Networks Chapter 13: Exploring Bias and Fairness Chapter 14: Analyzing Adversarial Performance Part 3 – DLOps
Chapter 15: Deploying Deep Learning Models to Production Chapter 16: Governing Deep Learning Models Chapter 17: Managing Drift Effectively in a Dynamic Environment Chapter 18: Exploring the DataRobot AI Platform Chapter 19: Architecting LLM Solutions Index Other Books You May Enjoy

Technical requirements

This chapter will cover a practical example to test out data drift techniques. We will be using Python 3.10 and, additionally, we will require the following Python libraries to be installed:

  • evidently
  • numpy
  • transformers==4.21.3
  • torch==1.12.0
  • syllables
  • audiomentations
  • datasets

The code files are available on GitHub: https://github.com/PacktPublishing/The-Deep-Learning-Architect-Handbook/tree/main/CHAPTER_17.

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Authors (1)

Profile icon Ee Kin Chin
LinkedIn
Ee Kin Chin is a Senior Deep Learning Engineer at DataRobot. He holds a Bachelor of Engineering (Honours) in Electronics with a major in Telecommunications. Ee Kin is an expert in the field of Deep Learning, Data Science, Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Python, Keras, Pytorch, and related technologies. He has a proven track record of delivering successful projects in these areas and is dedicated to staying up to date with the latest advancements in the field.
See other products by Ee Kin Chin

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