Data Science Agent Project

Overview

The Data Science Agent Project is designed to develop automated problem identification systems that detect and resolve operational issues in real-time. The project involves designing and implementing end-to-end data science pipelines for large-scale data processing, leveraging advanced AI models like LLaMA2 for generating insights, and performing image interpretation using Lava.

Key Features

• Automated Problem Identification: Systems designed to detect and resolve operational issues automatically.
• End-to-End Data Science Pipelines: Complete pipelines for large-scale data processing, from data collection to model deployment.
• Business Insights Generation: Utilization of LLaMA2 for generating actionable business insights and summarizing complex documents.
• Image Interpretation: Accurate visual data insights delivered through image interpretation using Lava.
• Query-Based QA Systems: General query-based systems to enhance information retrieval and provide users with relevant answers.
• Web Application Development: Creation and deployment of Django-based APIs and web applications integrated with MySQL for data management.

Technologies Used

• Python
• Django
• MySQL
• LLaMA2
• Lava
• Data Science Libraries (e.g., Pandas, NumPy, Scikit-learn)