AI-Assisted Programming for Web and Machine Learning (Paperback)

Christoffer Noring

ISBN 10: 1835086055 / ISBN 13: 9781835086056

Verlag: Packt Publishing Limited, Birmingham, 2024

Paperback. Speed up your development processes and improve your productivity by writing practical and relevant prompts to build web applications and Machine Learning (ML) modelsPurchase of the print or Kindle book includes a free PDF copyKey FeaturesUtilize prompts to enhance frontend and backend web developmentDevelop prompt strategies to build robust machine learning modelsUse GitHub Copilot for data exploration, maintaining existing code bases, and augmenting ML models into web applicationsBook DescriptionAI-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. Youll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, youll 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. Youll 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. Youll see how simpler and AI-powered agents work and discover tool calling.What you will learnSpeed up your coding and machine learning workflows with GitHub Copilot and ChatGPTUse an AI-assisted approach across the development lifecycle Implement prompt engineering techniques in the data science lifecycleDevelop 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 Who this book is forExperienced 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. AI-Assisted Coding and Machine Learning helps you build applications and ML models using prompts. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781835086056

Inhaltsangabe:

Speed up your development processes and improve your productivity by writing practical and relevant prompts to build web applications and Machine Learning (ML) models

Purchase of the print or Kindle book includes a free PDF copy

Key Features

• 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

Book 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.

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

Who this book is 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.

Table of Contents

1. It's a New World, One With AI Assistants, and You're Invited
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

(N.B. Please use the Read Sample option to see further chapters)

Über die Autorin bzw. den Autor: 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.

Bibliografische Details

Titel: AI-Assisted Programming for Web and Machine ...
Verlag: Packt Publishing Limited, Birmingham
Erscheinungsdatum: 2024
Einband: Paperback
Zustand: new