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In the journey of life, keep learning and strive.
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In the journey of life, keep learning and strive.

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mhadeli/README.md

Hussain Adeli

Data Scientist · Machine Learning · Applied AI

I design and ship machine learning systems end to end; from statistical modeling
and experiment design to production LLM applications.

9+ years across nonprofit, tech, and international development.


LinkedIn Linktree


Expertise

Customer Data Science: propensity scoring, churn prediction, segmentation, customer lifetime value

Experimentation: A/B test design, statistical inference, uplift measurement

NLP & LLMs: semantic search, document intelligence, transformer fine-tuning

RAG Systems: ingestion, embedding, vector retrieval, grounded question answering

AI Integration: LLM-powered features embedded into production data workflows

Forecasting: classical time series, deep learning, and transformer-based approaches


Stack

Python SQL pandas scikit-learn statsmodels PyTorch Hugging Face LlamaIndex LangChain Streamlit Git



Happy to collaborate – and to volunteer data science for causes that matter.

Pinned Loading

  1. LlamaIndexSearch LlamaIndexSearch Public

    A Streamlit-based application leveraging Llama Index for efficient vectorized document search and natural language querying.

    Python

  2. web-crawler web-crawler Public

    Web Crawl is a web application that allows you to scrape web pages and use Retrieval-Augmented Generation (RAG) to answer questions based on the scraped content.

    Python

  3. TimeGPT TimeGPT Public

    TimeGPT is a production-ready generative pretrained transformer for time series. It’s capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few …

    Jupyter Notebook 6 1

  4. AI-Sementic-Search AI-Sementic-Search Public

    Forked from OjasMittal/AI-Sementic-Search

    Python

  5. Deep-Learning-for-Time-Series-Forecasting Deep-Learning-for-Time-Series-Forecasting Public

    This project demonstrates the application of deep learning techniques for time series forecasting. The goal is to predict future values based on historical data using neural networks.

    Jupyter Notebook

  6. Open-Source-Models-with-Hugging-Face Open-Source-Models-with-Hugging-Face Public

    The notebook provides examples and explanations on how to utilize pre-trained models for these tasks without the need for permanent local storage.

    Jupyter Notebook