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  • Book Overview & Buying AI-Assisted Programming for Web and Machine Learning
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AI-Assisted Programming for Web and Machine Learning

AI-Assisted Programming for Web and Machine Learning

By : Christoffer Noring, Anjali Jain, Marina Fernandez, Ayşe Mutlu, Ajit Jaokar
4.9 (9)
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AI-Assisted Programming for Web and Machine Learning

AI-Assisted Programming for Web and Machine Learning

4.9 (9)
By: Christoffer Noring, Anjali Jain, Marina Fernandez, Ayşe Mutlu, Ajit Jaokar

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)
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3
Tools of the Trade: Introducing Our AI Assistants
23
Other Books You May Enjoy
24
Index

Introduction

In November 2022, ChatGPT arrived from seemingly nowhere. Over time, ChatGPT gained momentum, gradually evolving into a widely embraced tool. Eventually, millions actively incorporated ChatGPT into their workflows, leveraging its capabilities for generating insights, summarizing text, crafting code, and more.

Its arrival changed many people’s workflow and improved it a lot in tasks like quickly understanding large bodies of text, writing emails, and more. Here you are, having bought this book, and hoping that you can learn how to use an AI tool like ChatGPT or GitHub Copilot to make you more efficient. That’s exactly the mission of this book: to teach you not only how to use these two AI tools but also to be able to apply them across various problem domains.

Before we start solving problems using an AI assistant, let’s back up a bit; how did we get here? ChatGPT just didn’t arrive out of nowhere, right?

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83
Tech Concepts
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Programming languages
73
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AI-Assisted Programming for Web and Machine Learning
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