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dyerrington/README.md

Hi there 👋

Originally I am from Alaska but have lived in the San Francisco Bay area for almost 20 years. I've spent a lot of the past 5 years teaching people machine learning and Python while working at a mainstream bootcamp-type school. More recently I managed data science at a mobile gaming analytics startup from a hands-on role building prototype applications and deploying machine learning models at scale. Since the beginning of 2020, I've been consulting and contracting as a data scientist for a variety of projects related to traditional supervised learning, NLP, and working with students 1:1 from beginner to advanced ML topics.

When it comes to my professional interests, my favorite topics include machine learning, Python, and data visualization. My ideal day consists of learning something new, building ideas from the ground up in a Jupyter Notebook, and sharing when I've learned with others.

Currently, I'm working on:

  • Regularly updated Jupyter notebooks for learning ML and Data Science
  • A GPT2 model that generates terrible insults
  • Cleaning up a Django project that hosts a topic model about the compendium of rap music
  • Fun experiments with ML and magenta.js
  • Building an app to help life-sciences people find weather anomalies

My next big project that is close to being released is an open source library of content for anyone looking to learn Python for data science. I will post details sometime this Feb 2022.

Pinned Loading

  1. odscwest-dv-python odscwest-dv-python Public

    Jupyter Notebook 5 7

  2. kskk02/DataForDiploma kskk02/DataForDiploma Public

    Analysis and Web App for Data for Diploma Challenge

    HTML 1

  3. LDAExplorer LDAExplorer Public

    Python 4 1

  4. Plotting multiple figures with seabo... Plotting multiple figures with seaborn and matplotlib using subplots.
    1
    ##
    2
    # Create a figure space matrix consisting of 3 columns and 2 rows
    3
    #
    4
    # Here is a useful template to use for working with subplots.
    5
    #
  5. Ordinary least squares implemented w... Ordinary least squares implemented with numpy.
    1
    import numpy as np
    2
    import sys
    3
    
                  
    4
    # lines = input.split("\n")
    5
    lines = sys.stdin.readlines()
  6. Yerrington-Consulting/Ragtastic Yerrington-Consulting/Ragtastic Public

    Easily prototype and scale Retrieval-augmented generation apps with Ragtastic. Our intuitive UI simplifies managing vector databases and large language model integration, making advanced AI more ac…

    JavaScript