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Unleash the Potential of Datasets with Intelligent Tasks, Tutorials, and Algorithm Recommendations.

Project description

🧑‍🎓 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.

📈 Installation:

pip install ProTaska-GPT --upgrade

🚀 Usage:

Importing base descriptors and ideation bot:

from protaska.describer import describe_dataset
from protaska.ideate import main as chatbot

Providing meta-data about the dataset to be used:

openai_key = '**open-ai-secret-key**'
importer_type = "HuggingFaceDatasetImporter"
dataset_key = 'mteb/tweet_sentiment_extraction'
destination_path = './downloaded_data/'

Getting automated data descriptions:

description, dataloader_obj = describe_dataset(openai_key, importer_type, destination_path, dataset_key)
description

Running an interactive ChatBot for ideation and base-code building:

chatbot(openai_key, description, dataloader_obj.superficial_meta_data, agent_verbose=False)

💁 Contributing

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

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