🤖 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:
Complete Code: https://tinyurl.com/ycxk7cwr
Series Playlist: https://tinyurl.com/2766mwkw
⏱ 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:
Installing libraries with pip install -r requirements.txt
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
👉 Watch Episode 1 if you missed it: https://tinyurl.com/2ps3fm8u
Join this channel to get access to the perks:
/ @atefataya
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⚙️ Github Project for you to follow along in this tutorial:
1. Github Repository:
🔗 https://tinyurl.com/ycxk7cwr
⚙️ Related YouTube Tutorials:
1. AI Agents Playlist
🔗 https://tinyurl.com/2766mwkw
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⚙️ Links:
🔗 OpenAI: https://openai.com/
🔗 LangChain: https://www.langchain.com/
🔗 LangGraph: https://www.langchain.com/langgraph
🔗 ArXiv: https://arxiv.org/
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