LLM based data scientist, AI native data application. AI-driven infinite thinking redefines BI.

A curated list of 100+ resources for building and deploying generative AI specifically focusing on helping you become a Generative AI Data Scientist with LLMs

High performance, low friction LLM chat for data scientists

This hands-on walks you through fine-tuning an open source LLM on Azure and serving the fine-tuned model on Azure. It is intended for Data Scientists and ML engineers who have experience with fine-tuning but are unfamiliar with Azure ML.

The LLMAgentOps Toolkit is a repository that provides a foundational structure for building LLM Agent-based applications using the Semantic Kernel. It serves as a starting point for data scientists and developers, facilitating experimentation, evaluation, and deployment of LLM Agent-based applications to production.

A curated collection of interview questions and expert answers focused on Large Language Models (LLMs). Whether you're preparing for a Data Scientist, ML Engineer, or AI Researcher role, this repository is designed to help you crack interviews confidently in the rapidly evolving world of Generative AI.

This hands-on walks you through fine-tuning an open source LLM on Azure and serving the fine-tuned model on Azure. It is intended for Data Scientists and ML engineers who have experience with fine-tuning but are unfamiliar with Azure ML.

LLM API-Powered Job Listings Data Cleaning Tool: Showcase for Data Scientists

FeatureForge LLM is a Python package that leverages large language models (LLMs) to automate and enhance feature engineering processes. By utilizing advanced AI capabilities, this package helps data scientists and machine learning engineers discover, generate, and implement intelligent features across various datasets.

Welcome to the LLMs Interview Prep Guide! This GitHub repository offers a curated set of interview questions and answers tailored for Data Scientists. Enhance your understanding of Large Language Models, prepare for technical interviews, and excel in the evolving landscape of data science with a focus on LLM applications.

LLMs for Data Scientists

Course Notes - LLM Fine-Tuning for Data Scientists and Software Engineers

AI Data Scientist is an approach towards conversational, open-sourced Data Science analysis. Leveraging the power of LLMs and natural language to democratize data insights.

Data scientist lab run in Google Colab or locally in Anaconda using JupyterLab to experiment in creating AI agents in python using various Open Source and Frontier LLM models. Projects include RAG, inference, function calling and multi-modal techniques.

This NLP project leverages a quantised LLM to read and correct text extracted from PDFs. Ideal for students, professionals, and data scientists, it helps clean up and organize text data from various documents. Built to run even on small GPUs with 8GB VRAM, it's a fun learning project aimed at making PDF text extraction smarter and cleaner.

A hands-on guide to building, deploying, and scaling AI/ML solutions. Includes tutorials on LLMs, real-time AI, data engineering, and model serving with FastAPI, MLflow, and Docker. Designed for developers and data scientists tackling real-world AI challenges.

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Notebook Data Scientist using LLM (PoC)

Hands-on

resources for data scientists to start incorporating LLMs into their workflows

Autonomous data scientist that helps developers building LLM-based systems understand and work with unstructured data.

FTzard, a comprehensive framework designed to assist data scientists in managing their LLM experiments. FTzard offers an end-to-end continual learning pipeline, integrating orchestration with Dagster, experiment and model tracking with MLflow, assurnig environment reproducibility with Pixi, and data versioning with DVC & More!

Data Cleanser and (soon to be visualizer) as a CodeAgent on Sandbox PC, using E2B, Lang, Opentelemetry (tba). Cleaning huge amounts of data is very tricky using small local models, so i use an agentic loop with refreshing context and dynamic RAG so it can record and recall insights. Smolagents use undocumented in-line with Hugging Face ethics.

AI Developer & Data Scientist — Python, ML, LLMs, XGBoost

Data Scientist with expertise in LLMs, AWS, and Power BI

AI Data Scientist Agent with Gemini LLM - Automated EDA, Statistical Testing, Data Cleaning, and AutoML

A retrieval-grounded LLM assistant that answers questions about my CV and professional motivation as a Data Scientist, in any language.

this is an interactive Streamlit web application that assists with data analysis, exploratory data analysis (EDA), LLM-powered data chat, and automated machine learning (AutoML). This tool is perfect for analysts and data scientists looking for a no-code/low-code interface for working with datasets

Data Scientist & AI Developer specializing in Python, R, and LLM applications. I build intelligent systems that solve real-world problems—from predictive modeling to RAG agents. Passionate about sustainable tech and data-driven insights. 📍 Germany | 🎓 NVIDIA Certified |

DataFlowLab est une application Python locale et modulaire permettant aux data scientists de créer visuellement des pipelines ML par drag-and-drop, avec EDA automatisée, génération de code et assistance par LLM local.