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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

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835086056
Length 602 pages
Edition 1st Edition
Languages
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Authors (5):
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Marina Fernandez Marina Fernandez
Author Profile Icon Marina Fernandez
Marina Fernandez
Ajit Jaokar Ajit Jaokar
Author Profile Icon Ajit Jaokar
Ajit Jaokar
Anjali Jain Anjali Jain
Author Profile Icon Anjali Jain
Anjali Jain
Christoffer Noring Christoffer Noring
Author Profile Icon Christoffer Noring
Christoffer Noring
Ayşe Mutlu Ayşe Mutlu
Author Profile Icon Ayşe Mutlu
Ayşe Mutlu
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Toc

Table of Contents (25) Chapters Close

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

The new paradigm, programming with natural language

Probably the biggest game changer with using LLM-based AI assistants is that you’re able to interact with them using nothing but natural language. There’s no need to learn a programming language to get the response you need. This change constitutes a new paradigm in interacting with AI. We’re moving away from writing in specific languages for producing apps, data retrieval, or even how we produce images, presentations, and more to express at a high level what we want through a prompt.

Here is an example of things that are now possible to do using prompts, where it before needed considerably more effort:

  • Programming: With a prompt, you express what app you want to build or what changes you want to make with the code.
  • Image generation: Where you before needed a designer or artist, you can now generate via prompts.
  • Videos: There are tools out there that, once given a prompt, will generate videos where an avatar reads out your written text.
  • Text tasks: LLM-based AI assistants can generate emails, summarize large bodies of text, author interview ads, and much more; anything you can imagine with text really.

All these application areas mentioned above make it clear that LLM-based AI tools are useful not only to programmers and data scientists but numerous different professions.

Challenges and limitations

Is everything working perfectly at this point? AI assistants aren’t able to replace “you” just yet, and should be considered more of a “thinking partner.” Microsoft has even, through conscious naming, called their AI assistants “Copilots” where you’re clearly the pilot that sets out the direction. These tools can generate text and other modalities in seconds, but you need to verify the correctness. Often, the first response you get from a tool is something you need to iterate over. The good news is that it just takes seconds to redo the instruction.

An important thing to realize about AI assistants is that the more skilled you are at a certain topic, the more intelligent questions you can ask of it, and you’ll be able to better assess the correctness of the response.

You have been reading a chapter from
AI-Assisted Programming for Web and Machine Learning
Published in: Aug 2024
Publisher: Packt
ISBN-13: 9781835086056
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