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jordandeklerk/README.md

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Summary

Having recently graduated with a Master of Science degree in Statistics from the University of Illinois Urbana-Champaign in May 2024, I have developed a robust foundation in various statistical and computer science disciplines, including deep learning, computer vision, and Bayesian machine learning. Additionally, I hold a Master of Science degree in Economics from the University of Wisconsin-Madison, where I specialized in applied econometrics and causal inference.

Before my recent academic pursuits, I accumulated five years of experience as a data scientist in the healthcare industry, focusing on developing transformer models, latent variable models, causal inference models, and time series forecasting models.

Highlights

📖 Completed Master's in Statistics @ The University of Illinois Urbana-Champaign.

📖 Completed Master's in Economics @ The University of Wisconsin-Madison.

💻 Currently building open-source projects in graph transformer models, LLMs, causal models, and time-series forecasting.

🖥️ Selected Open-Source Projects

Machine Learning
Title Stars Technologies
EHR-BERT Stars PyTorch
Amortized Bayes Stars PyTorch
OpenCodeInterpreter-DS-6.7B-Finetune Stars PyTorch
Swin Transformer Stars PyTorch
Starcoder2-3B-Finetune Stars PyTorch

Pinned

  1. EHR-BERT EHR-BERT Public

    BERT model on CMS synthetic EHR data for diagnosis and procedure prediction in PyTorch

    Python

  2. Amortized-Bayes Amortized-Bayes Public

    Closing the amortization gap in Bayesian deep generative models (A-VI vs F-VI) in PyTorch

    Jupyter Notebook

  3. OpenCodeInterpreter-Finetune-SQL OpenCodeInterpreter-Finetune-SQL Public

    Finetuning OpenCodeInterpreter-DS-6.7B for Text-to-SQL Code Generation on a Single A100 GPU

    Jupyter Notebook 1

  4. SwinViT SwinViT Public

    Implementing a Swin Transformer model in PyTorch on CIFAR-10

    Python 2