Build an AI Research Agent: Data Extraction & Setup | Episode 02

🤖 Learn how to build an AI that can read and understand scientific papers! In this tutorial, you'll create a Python program that automatically extracts and processes research papers from ArXiv. Perfect for developers interested in AI, data science, and automation.

✨ *What You'll Learn:*
- How to access ArXiv's vast research database
- Building a robust data extraction pipeline
- Processing and storing scientific papers
- Working with JSON and Pandas for data analysis

🎯 *Prerequisites:*
- Basic Python knowledge
- Watched Part 1: [link]
- Git installed

⚡️ *Quick Links:*

⏱ *Timestamps:*
00:06 Introduction
00:54 ArXiv Overview
02:22 Data Extraction
05:40 Testing
07:36 Wrap-up

*In this episode, we take a big step forward by:*
✅ Installing all the necessary libraries for our project
✅ Introducing ArXiv – what it is and why it's a vital resource for researchers
✅ Writing a Python function to extract data from ArXiv
✅ Saving the data into a JSON file and exploring it with Pandas

This tutorial is packed with hands-on code demonstrations and clear explanations to help you get started on your journey to building powerful AI research tools.

💡 *Topics Covered:*
- Fetching and processing research papers from ArXiv
- Exporting data to JSON format
- Displaying and sampling data with Pandas

If you're interested in AI, data science, or Python programming, this series is for you! 💻🔥

📌 *Don't forget to:*
👍 Like the video if you found it helpful
📝 Drop your questions or feedback in the comments
🔔 Subscribe to the channel and hit the notification bell to stay updated on future episodes

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⚙️ *Github Project for you to follow along in this tutorial:*
1. *Github Repository:*

⚙️ *Related YouTube Tutorials:*
1. *AI Agents Playlist*
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⚙️ *Links:*
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[atefataya]

🚀 Welcome to Episode 2 of the AI Research Agent Series! 🎉

In this tutorial, we’ll take a deep dive into:
✅ Installing essential libraries 📦
✅ Introduction to ArXiv and its importance 📚
✅ Extracting data, saving it as JSON, and analyzing it with Pandas 📊

Got questions or stuck on any step? Drop them in the comments, and I’ll be here to help! 💬

If you’re finding this series helpful, don’t forget to like 👍, subscribe 🔔, and share with others passionate about AI and data science! 💻✨

What’s your favorite part so far? Let me know! 👇

[wilburtcavalari]

Can HasData be used for scraping data from ArXiv like in this tutorial?