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Researching how semantics influence generalization in object-centric reinforcement learning.
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See-Through-Spots-Eyes
August 21, 2024 – August 28, 2024
A Computer Vision Project to demonstrate various augmentations and overlays of streamed video
View ProjectDQN
June 1, 2024 – June 7, 2024
A replication of the Deep Q-Network Algorithm as seen in "Human-level control through deep reinforcement learning" - Mnih et. al. 2015
View ProjectModel-Free-Learning
May 30, 2024 – May 31, 2024
An implementation of model-free learning techniques including SARSA, Q-Learning and SARSA-Lambda
View ProjectCNNs-for-Image-Classification
May 27, 2024 – May 28, 2024
A Pytorch implementation of Convolutional Neural Networks, using LeNet5 for Image Classification
View ProjectMulti-Layered-Perceptron
May 24, 2024 – May 31, 2024
A python implementation of a feed forward neural network from first principles. The network is trained via gradient descent and backpropagation on the MNIST dataset.
View ProjectDynamic-Programming
May 20, 2024 – May 23, 2024
A python implementation of dynamic programming methods to solve the Bellman Equation.
View ProjectLogistic-Regression
May 16, 2024 – May 20, 2024
Implementation of Logistic Regression from first principles in python. For binary classification.
View ProjectMulti-Armed-Bandits
May 15, 2024 – May 15, 2024
A python implementation of the multi-armed bandit problem using reinforcement learning. The repo contains implementations of the epsilon greedy, optimistic initialization and upper confidence bound (UCB) methods.
View ProjectRL-Project--Minihack-Quest-Hard-v0
November 9, 2021 – January 15, 2022
This Github repository serves as the source code for completing the Minihack-Quest-Hard-v0 using Reinforcement Learning
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal and heavily focused on academic/theoretical implementations of machine learning algorithms. While demonstrating technical interest, there is no evidence of collaborative work, diverse project types (e.g., industry applications, data engineering, MLOps), or experience outside of pure algorithm implementation. This suggests a potential gap in understanding real-world data science workflows and team environments, which might impact cultural fit for a senior role requiring broader contributions.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.