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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
Author (1):
Ee Kin Chin Ee Kin Chin
Profile icon Ee Kin Chin

Table of Contents (25) Chapters

Preface 1. Part 1 – Foundational Methods
2. Chapter 1: Deep Learning Life Cycle 3. Chapter 2: Designing Deep Learning Architectures 4. Chapter 3: Understanding Convolutional Neural Networks 5. Chapter 4: Understanding Recurrent Neural Networks 6. Chapter 5: Understanding Autoencoders 7. Chapter 6: Understanding Neural Network Transformers 8. Chapter 7: Deep Neural Architecture Search 9. Chapter 8: Exploring Supervised Deep Learning 10. Chapter 9: Exploring Unsupervised Deep Learning 11. Part 2 – Multimodal Model Insights
12. Chapter 10: Exploring Model Evaluation Methods 13. Chapter 11: Explaining Neural Network Predictions 14. Chapter 12: Interpreting Neural Networks 15. Chapter 13: Exploring Bias and Fairness 16. Chapter 14: Analyzing Adversarial Performance 17. Part 3 – DLOps
18. Chapter 15: Deploying Deep Learning Models to Production 19. Chapter 16: Governing Deep Learning Models 20. Chapter 17: Managing Drift Effectively in a Dynamic Environment 21. Chapter 18: Exploring the DataRobot AI Platform 22. Chapter 19: Architecting LLM Solutions 23. Index 24. Other Books You May Enjoy

Technical requirements

We will have a practical topic in this chapter to make predictions using a DataRobot deployed model. We will be using Python 3.10 and we will require the following Python libraries to be installed:

  • datarobotx==0.1.17
  • pandas==2.0.3

The code files are available on GitHub at https://github.com/PacktPublishing/The-Deep-Learning-Architect-Handbook/tree/main/CHAPTER_18, and the dataset can be downloaded from https://www.kaggle.com/datasets/dicksonchin93/datarobot-compatible-house-pricing-dataset.

Additionally, a paid or free trial account is needed to access DataRobot. To subscribe for a trial account, do the following:

  1. Visit the DataRobot website at https://www.datarobot.com/trial/.
  2. Fill up your credentials under the Start For Free interface on the right side of the web page and click on the Submit button.
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