Metadata-Version: 2.1
Name: ProTaska-GPT
Version: 0.0.9
Summary: Unleash the Potential of Datasets with Intelligent Tasks, Tutorials, and Algorithm Recommendations.
Home-page: https://github.com/AmanPriyanshu/protaska-gpt
Author: Aman Priyanshu, Supriti Vijay
Author-email: amanpriyanshusms2001@gmail.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: langchain
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: colorama
Requires-Dist: wikipedia
Requires-Dist: openai
Requires-Dist: datasets
Requires-Dist: tiktoken

# 🚀 ProTaska-GPT

**Your AI-powered data companion 🤖**


Specify your dataset of choice, and ProTaska-GPT generates a tailored codebase, empowering you to visualize and understand the dataset with tasks, tutorials, and actionable insights. Accelerate your data science journey with ease and efficiency!

## 🖊️ Key Features:

1. **Dataset Ingestion:** ProTaska-GPT seamlessly integrates with dataset sources like Kaggle and Hugging Face (_for now_), allowing users to easily import and work with diverse datasets.
2. **Task Recommendations:** Leveraging its GPT-backbone, it generates a customized set of tasks tailored to each dataset, providing users with valuable project ideas and challenges.
3. **Algorithm Suggestions:** Based on the dataset characteristics, it suggests suitable machine learning algorithms, enabling users to make informed decisions during their project journey.
4. **Conversational Chatbot:** Allow user to discuss about different techniques and scrape information from Wikipedia to give relevant responses.

## 🔎 Objectives:
1. **Beginner-Friendly Tutorials**: ProTaska-GPT aims to offer automated generation of a collection of beginner-friendly tutorials that guide users through common data science workflows, step-by-step, fostering practical learning and skill development.

## 💁 Contributing

This is an open-source project and we would be really grateful to any contributions.
