www.braintank.ca

Author: JonathanVinden

  • Overview of Teaching Assistant Jobs

    Overview of Teaching Assistant Jobs

    University of Guelph Statistical Learning Centre

    • Tutoring as a member of the Statistics Learning Centre.
    • In charge of organizing discussion, responding to questions, and
    • developing an engaging space for learning for students in statistics.
    • Practicing effective communication of complex ideas to students with many questions.

    MATH*1080: Elements of Calculus I Undergraduate Teaching Assistant

    • I was given the responsibilities of invigilating labs and exams, grading student assignments, and exams for a Calculus I class.

    Collaborators: Dr. Lorna Deeth, and Dr. Daniel Kraus

    Job Title: Teaching Assistant

    University: University of Guelph

  • 101 Introduction to Python Class

    101 Introduction to Python Class

    Description:

    These videos were made to help students in introduction data science and introduction biology at Western University to introduce python computing into their respective fields. Prep 101 is an online prep class that helps student excel in a variety of classes.

    For this project, I had the tasks of:

    1. Creating the curriculum to cover all functionality students need to thrive in their respective classes. This includes python basics, displaying and processing data, all the way up to solving partial differential equations with python packages.
    2. Creating coding tutorial videos which effectively communicated the core principles.
    3. Producing worksheets with questions and solutions that helped students apply the concepts in the video to enhance their coding abilities.
    4. I had to opportunity to communicate with students one-on-one and help guide their inquiry.
    Lesson One:
    Lesson Two:
    Lesson Three:
    Lesson Four:
    Worksheets and Resources:

    Worksheet questions 1 (with solutions).pdf

    Worksheet questions 1.pdf

    Worksheet_questions2.pdf

    Worksheet_questions3.pdf

    Company: Prep 101 (prep101.com)

    Job Title: Python instructor and curriculum builder

  • Deep Counterfactual Regret Minimization in a Multi-AgentIncomplete Information Game of “Take 5”

    • Take-5 is a multi-agent repeating imperfect-information normal-form tabletop card game. Players aim to anticipate their opponents’ moves and strategize with the cards in their hand to optimize their outcomes and maximize utility.
    • Based on a paper “Deep Counterfactual Regret Minimization” by N. Brown et al. I adapted it to allow for the agent to accurately predict counterfactual regret vectors for this game.
    • With lack of better assessment, the agent was able to beat my group of friends who play the game very often.
  • Everybody has a Chess AI… Here’s Mine

    Everybody has a Chess AI… Here’s Mine

    Work was based on “mastering chess and shogi by self-play with a general reinforcement learning algorithm”.

    • Used a game matrix to map the state of the game, and a CNN to predict the utility of average moves.
    • To solve a sparse-reward problem, I started by optimizing the RL algorithm to take as many opponent pieces as possible, then to take as many pieces as possible without losing own pieces, and then finally optimized it to win the game.
    • Algorithm performed decently, but had clear strategic flaws. I was limited in compute for this project.