AI-Assisted Programming for Web and Machine Learning.epub

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

Author(s): Christoffer Noring

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

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.

This curse 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