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Book Overview & Buying
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Table Of Contents
AI-Assisted Programming for Web and Machine Learning
By :
AI-Assisted Programming for Web and Machine Learning
By:
Overview of this book
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.
Table of Contents (25 chapters)
Free Chapter
It’s a New World, One with AI Assistants, and You’re Invited
Prompt Strategy
Tools of the Trade: Introducing Our AI Assistants
Build the Appearance of Our App with HTML and Copilot
Style the App with CSS and Copilot
Add Behavior with JavaScript
Support Multiple Viewports Using Responsive Web Layouts
Build a Backend with Web APIs
Augment Web Apps with AI Services
Maintaining Existing Codebases
Data Exploration with ChatGPT
Building a Classification Model with ChatGPT
Building a Regression Model for Customer Spend with ChatGPT
Building an MLP Model for Fashion-MNIST with ChatGPT
Building a CNN Model for CIFAR-10 with ChatGPT
Unsupervised Learning: Clustering and PCA
Machine Learning with Copilot
Regression with Copilot Chat
Regression with Copilot Suggestions
Increasing Efficiency with GitHub Copilot
Agents in Software Development
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Index
