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dvukolov/README.md

Hi there 👋

I'm a data analyst passionate about coding in Python, R, and Go.

Some of my projects include:

Calibrated Uncertainty (NumPy, SciPy, scikit-learn, PyMC3, JAX-based NumPyro)

  • Conducted in-depth analysis of an uncertainty calibration algorithm for Bayesian neural networks.
  • Identified the advantages of the approach and its modes of failure.
  • Received the highest grade and an invitation to continue research at the Harvard Data to Actionable Knowledge lab.

Galaxy Measurements (TensorFlow, pandas, Streamlit, Docker, Heroku)

  • Used TensorFlow to estimate the shape and brightness of simulated galaxies.
  • Responsible for data generation, exploratory data analysis web app, neural architecture search, and denoising pipelines.
  • Got the top grade and an opportunity to continue research.

NBA Conference Advantage (R, tidyverse, Scrapy, LaTeX)

  • Performed statistical modeling of potential bias in the NBA that grants teams in one conference an easier path to success due to the differences in travel and schedule.
  • Wrote web scrapers, feature engineering, and most of the analysis code in R.
  • Built linear regression models, ran diagnostics, authored around 70% of the report.

Meteorological Observatory (Python, TCP sockets, regex, pytest)

  • Implemented in Python streaming data collection from weather instruments.
  • The code has a suite of unit tests and is deployed at a university meteorological station.
  • Serves as the basis for experimental studies of turbulence by five scientific institutions.

Open Source Projects (Python, R, C/C++)

  • Contributed with bug fixes and documentation updates to open source projects such as Apache Arrow, scikit-learn, ThunderSVM (GPU accelerated SVM), Picasso (sparse regression algorithm), Gap Statistic (clustering metric).

Pinned Loading

  1. calibrated-uncertainty calibrated-uncertainty Public

    Forked from 0-one/AM207_Project_Deep_Learning_Uncertainties_Calibration

    Analysis of the uncertainty calibration algorithm for Bayesian neural networks

    Jupyter Notebook 1

  2. nba-conference nba-conference Public

    Statistical modeling of NBA conference bias due to differences in travel and schedule

    TeX

  3. measure-galaxies measure-galaxies Public

    Estimating the shape and flux of galaxies with neural networks

    Jupyter Notebook 3

  4. alexavr/tower_parse alexavr/tower_parse Public

    Eddy Covariance Tower(s). Extract measurements from streaming meteorological devices and transmit them to the central project server for batch processing.

    Python 1