SiddharthThakar

AutoDS — autonomous data scientist

A full-stack AutoML application that takes a raw table or a time series and returns a finished analysis: exploratory profiling, preprocessing, model training, diagnostics, explainability, a written report, and an inference endpoint. Built so an analyst can reach a defensible model without hand-writing the same forty notebook cells again.

Stack

Python, Streamlit, FastAPI, PostgreSQL, Docker

Covers

Tabular ML and time-series forecasting

Role

Design, build and deployment

Canada Labour & Affordability Intelligence

An analytics platform that joins Job Bank, Statistics Canada and CMHC data so you can compare Canadian cities on the things that decide where you move: which occupations are hiring, what they pay, what rent does to that wage, and where the trend is heading. Includes forecasts and automated data-quality checks that flag a source before it quietly breaks a report.

Stack

Power BI, DAX, PostgreSQL, Python

Sources

Job Bank, Statistics Canada, CMHC

Role

Data model, ETL, report design

Ask a PDF, get a cited answer

A retrieval-augmented question answering system for documents that runs entirely on your own machine — Ollama embeddings, ChromaDB retrieval, a re-ranking pass to cut weak matches, and Llama 3.2:3b for generation. No document ever leaves the laptop, which is the point.

Stack

Python, Streamlit, Ollama, ChromaDB, Llama 3.2:3b

Focus

Retrieval quality and re-ranking

Role

Solo build