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AI-Assisted Programming for Web and Machine Learning

You're reading from AI-Assisted Programming for Web and Machine Learning Improve your development workflow with ChatGPT and GitHub Copilot

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835086056

Length 602 pages

Edition 1st Edition

Languages

Python

Tools

ChatGPT

Concepts

Artificial Intelligence

Authors (5):

Christoffer Noring

Anjali Jain

Marina Fernandez

Ayşe Mutlu

Ajit Jaokar

+1 more

View More author details

Table of Contents (25) Chapters

Preface

1. It’s a New World, One with AI Assistants, and You’re Invited FREE CHAPTER

2. Prompt Strategy

3. Tools of the Trade: Introducing Our AI Assistants

4. Build the Appearance of Our App with HTML and Copilot

5. Style the App with CSS and Copilot

6. Add Behavior with JavaScript

7. Support Multiple Viewports Using Responsive Web Layouts

8. Build a Backend with Web APIs

9. Augment Web Apps with AI Services

10. Maintaining Existing Codebases

11. Data Exploration with ChatGPT

12. Building a Classification Model with ChatGPT

13. Building a Regression Model for Customer Spend with ChatGPT

14. Building an MLP Model for Fashion-MNIST with ChatGPT

15. Building a CNN Model for CIFAR-10 with ChatGPT

16. Unsupervised Learning: Clustering and PCA

17. Machine Learning with Copilot

18. Regression with Copilot Chat

19. Regression with Copilot Suggestions

20. Increasing Efficiency with GitHub Copilot

21. Agents in Software Development

22. Conclusion

23. Other Books You May Enjoy

24. Index

Assignment

Find a piece of code you want to improve. Follow the process outlined in this chapter to:

Identify the problems. What problems do you see?
Add tests and de-risk changes.
Implement the changes and improve maintainability.

If you don’t have a piece of code you want to improve, try using the code from this chapter or the code from the Kata (Gilded Rose) GitHub page: https://github.com/emilybache/GildedRose-Refactoring-Kata.

The rest of the chapter is locked

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Authors (5)

Christoffer Noring

Christoffer Noring

Christoffer Noring works as a Senior Advocate at Microsoft and focuses on application development and AI. He's a Google Developer Expert and a public speaker on 100+ presentations across the world. Additionally, he's a tutor at the University of Oxford on cloud patterns and AI. Chris is also a published author on Angular, NGRX, and programming with Go.

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Anjali Jain

Anjali Jain

Anjali Jain is a London-based AI and ML professional with a career spanning over two decades. Currently working as a data architect for Metrobank, she brings her expertise in AI, data, architecture, data governance, and software development to the financial sector. Anjali holds a bachelor's degree in electrical engineering and boasts certifications, including TOGAF 9.1 and ITIL 2011 Foundation. In her role as Senior AI and ML tutor at Oxford, she shares cutting-edge knowledge on various technologies.

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Marina Fernandez

Marina Fernandez

Marina Fernandez is a data science and Databricks consultant with expertise in financial risk management. She contributes to the academic team at the University of Oxford, where she holds the positions of senior AI and ML tutor and guest lecturer. Throughout her 20-year career, Marina has worked on the development of large-scale enterprise systems for various business domains. Her experience encompasses e-commerce, e-learning, software security, commodity trading, commodity trading and risk management systems, and regulatory reporting. Marina obtained her MSc in Software Engineering from the University of Oxford. Additionally, she has earned professional certifications, including Microsoft Certified Professional and Certified Scrum Master

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Ayşe Mutlu

Ayşe Mutlu

Ayşe Mutlu is a data scientist working on Azure AI and DevOps technologies. Based in London, Ayşe's work involves building and deploying Machine Learning and Deep Learning models using the Microsoft Azure framework (Azure DevOps and Azure Pipelines). She enjoys coding in Python and contributing to open-source initiatives in Python.

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Ajit Jaokar

Ajit Jaokar

Ajit Jaokar is a data scientist for Feynlabs, building AI prototypes for complex applications. He is also a course director for AI at the University of Oxford. Besides this, Ajit is a visiting fellow in Engineering Sciences at the University of Oxford and conducts AI courses at the London School of Economics, Universidad Politecnica de Madrid, and the Harvard Kennedy School of Government as part of The Future Society. His work at Oxford and his company is based on interdisciplinary aspects of AI, including AI with digital twins, quantum computing, metaverse, Agtech, and life sciences. His teaching is based on a methodology for AI and cyber-physical systems, which he is developing as part of his research.

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