Setting Up NIFTY 50 : DBERT Labs Summer Internship Project

How to Set Up the NIFTY 50 AI Predictor Locally | DBERT Labs Internship

Welcome, interns! 🚀 Before we begin upgrading our AI trading systems for the May 2026 Summer Batch, you need to get the current baseline project up and running on your local machines.

In this video, our Lead Mentor walks you through the step-by-step local setup for the NIFTY 50 AI Stock Predictor
. This enterprise-grade machine learning application is optimized for Python 3.12 and features a "Zero Configuration Setup" so you can start coding in under 3 minutes
!
📌 What You Will Learn in This Video:
Step 1: Fork & Clone: How to fork the Digital-Blinc-DBERT / nifty50_predictor repository to your personal GitHub account
.
Step 2: The Emergency Launcher: How to use the run_app.bat or EMERGENCY_LAUNCHER.py scripts to instantly bypass painful package errors (like setuptools, pandas, and pkgutil) and launch the Streamlit dashboard on your localhost
.
Step 3: Start Contributing: How to create your first feature branch (git checkout -b feature/your-feature-name), commit your code, and submit a Pull Request back to the main repository
.
🔗 Important Links:
GitHub Repository: Digital-Blinc-DBERT/nifty50_predictor
Internship Portal: https://internship.dbert.online/
📚 Documentation Mentioned: Be sure to check the repository for additional help, including the README.md, TROUBLESHOOTING.md, and API_DOCS.md files
.
📧 Need Help? If you get stuck during the setup process, reach out to your mentor or email us at internship@digitalblinc.in
.
Fork. Launch. Build. Let’s get to work!
#DBERTLabs #AIInternship #MachineLearning #Python312 #Streamlit #GitHubSetup #CodingTutorial #StockPredictor #NIFTY50 #SoftwareEngineering

Видео Setting Up NIFTY 50 : DBERT Labs Summer Internship Project канала Digital Blinc