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AI-Assisted Programming for Web and Machine Learning
AI-Assisted Programming for Web and Machine Learning

AI-Assisted Programming for Web and Machine Learning: Improve your development workflow with ChatGPT and GitHub Copilot

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Profile Icon Christoffer Noring Profile Icon Anjali Jain Profile Icon Marina Fernandez Profile Icon Ayşe Mutlu Profile Icon Ajit Jaokar +1 more Show less
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$38.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (9 Ratings)
eBook Aug 2024 602 pages 1st Edition
eBook
$38.99
Paperback
$47.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Christoffer Noring Profile Icon Anjali Jain Profile Icon Marina Fernandez Profile Icon Ayşe Mutlu Profile Icon Ajit Jaokar +1 more Show less
Arrow right icon
$38.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (9 Ratings)
eBook Aug 2024 602 pages 1st Edition
eBook
$38.99
Paperback
$47.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$38.99
Paperback
$47.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Utilize prompts to enhance frontend and backend web development
  • Develop prompt strategies to build robust machine learning models
  • Use GitHub Copilot for data exploration, maintaining existing code bases, and augmenting ML models into web applications

Description

AI-Assisted Programming for Web and Machine Learning shows you how to build applications and machine learning models and automate repetitive tasks. Part 1 focuses on coding, from building a user interface to the backend. You’ll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, you’ll build a web API with Python and Flask and refactor the code to improve code readability. Part 1 ends with using GitHub Copilot to improve the maintainability and performance of existing code. Part 2 provides a prompting toolkit for data science from data checking (inspecting data and creating distribution graphs and correlation matrices) to building and optimizing a neural network. You’ll use different prompt strategies for data preprocessing, feature engineering, model selection, training, hyperparameter optimization, and model evaluation for various machine learning models and use cases. The book closes with chapters on advanced techniques on GitHub Copilot and software agents. There are tips on code generation, debugging, and troubleshooting code. You’ll see how simpler and AI-powered agents work and discover tool calling.

Who is this book for?

Experienced developers new to GitHub Copilot and ChatGPT can discover the best strategies to improve productivity and deliver projects quicker than traditional methods. This book is ideal for software engineers working on web or machine learning projects. It is also a useful resource for web developers, data scientists, and analysts who want to improve their efficiency with the help of prompting. This book does not teach web development or how different machine learning models work.

What you will learn

  • Speed up your coding and machine learning workflows with GitHub Copilot and ChatGPT
  • Use an AI-assisted approach across the development lifecycle 
  • Implement prompt engineering techniques in the data science lifecycle
  • Develop the frontend and backend of a web application with AI assistance 
  • Build machine learning models with GitHub Copilot and ChatGPT 
  • Refactor code and fix faults for better efficiency and readability 
  • Improve your codebase with rich documentation and enhanced workflows 

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 30, 2024
Length: 602 pages
Edition : 1st
Language : English
ISBN-13 : 9781835083895
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OpenAI
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Product Details

Publication date : Aug 30, 2024
Length: 602 pages
Edition : 1st
Language : English
ISBN-13 : 9781835083895
Vendor :
OpenAI
Category :
Languages :
Concepts :

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(9 Ratings)
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N/A Oct 14, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book reference for developers who want understanding utility of developing software with generative artificial intelligence.
Feefo Verified review Feefo
Banachan Oct 15, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book gives a great progression of the topics in regard to LLMs and use cases. It starts with the basic principles and premises and goes into more details chapter by chapter. So if you want a broad landscape perspective of use LLMs especially on how it is applied in chats, assistants, and used to help generate regression, classification unsupervised, and even deep learning models, etc. this is a good book to get and utilize for your purposes. It gives a good grounding on the world of LLMs and how to apply it by walking you through its practical applications and approaches.While not as deep technically as I would have hoped, it gives a good grounding on what to expect for such a new field in AI. Concepts on how apply LLMs in prompting, front and back end web app dev using assistants, data analysis are covered in enough detail. If you're already familiar with traditional classification and regressions modeling, it also covers how do it with LLMs. It blends both the traditional and newer methods to give you a sense on how to leverage what you already know with LLM based approaches. The code generation assistants make for a good exercise to accelerate your machine learning coding efforts.In all these of course, you need to have a good understanding of machine learning to begin with, as depending 100% on AI is not a panacea for good machine learning modeling expertise to apply in the real world. A small bonus content is that the book also covers Agentic processes in software development. Since this area is so new (as of this writing), a good basic introduction on the concepts were discussed.Overall, a good read providing a good virtual roadmap on how to do traditional machine learning using more cutting -edge tools and assistants. Highly recommended book and must read for those getting into the LLM field.
Amazon Verified review Amazon
saandeep sreerambatla Oct 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As a developer curious about leveraging AI in my workflow, "AI Assisted Programming for Web and Machine Learning" was a refreshing deep dive into the world of AI-assisted coding. Initially unsure of how tools like GitHub Copilot or ChatGPT would mesh with my development process, the book's clear, hands-on tutorials made the transition seamless.What I appreciated most was the practical application—building full web apps while integrating machine learning models, all enhanced by AI-generated code. The focus on real-world scenarios helped me see how these tools could drastically boost productivity.The section on prompt engineering is particularly insightful, teaching you how to effectively guide AI for more precise outcomes. This book doesn’t just show you how to use AI but pushes you to critically evaluate the results and refine your approach. I found the machine learning sections equally useful, especially for data exploration and model optimization, making it relevant for both web developers and data scientists alike.For anyone wondering if AI tools can fit into their workflow, this book is an essential guide. It's thorough but accessible, designed to give both beginners and seasoned developers the skills to harness AI and improve efficiency across projects.
Amazon Verified review Amazon
Andre Thomas Sep 20, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
AI is the future so you’d better start getting acquainted with it.I was excited to get to review AI-Assisted Programming for Web and Machine Learning (AAPWML) because I recently started incorporating ChatGPT into my workflow. It has been a wonderful tutor when I need explanations and when I need examples for concepts and keywords I never heard of or used.If you’re new to GPTs and LLMs and want to figure out how to incorporate it into your workflow then AAPWML is a great resource to have on the shelf. In the beginning, it gives a baseline understanding of what GPTs, LLMs, and NLPs are. Not necessarily required knowledge but good for curious minds.You then move on to the bread and butter of the book: how to communicate with them. I initially thought this was a straight forward task but you’ll soon find out that there’s an art to it. Further, there’s a strategy to having these GPTs help you—also another process that many might think is straight forward. And, hey, maybe it is for some very seasoned pros but not for all. This book helps you tackle that challenge as well by going step-by-step through building an e-commerce application.What I didn’t like about the book is that the writers use Github Copilot to build the application. I have nothing against it just that it is a paid tool. Even though it’s a $10/month for personal use, I think it would have been better to use a free tool so that no one has to pay to follow along with this book. Obviously, there are ways around this but I just thought it worth mentioning.Nonetheless, I think the book is well written and will help anyone get started on pair programming with AI tools.
Amazon Verified review Amazon
Sharan Shirodkar Sep 23, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A comprehensive resource for developers seeking to enhance their web and machine learning projects with AI-driven tools. Highly recommended
Amazon Verified review Amazon
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