kennethZhangML

AerialDroneProject

AerialSegU-Net

Repository for Code involving the development and training of U-Net for Aerial Drone Image Segmentation

ArbNet

ArbNet : Dynamic Data Structure designed for Quants, Researchers, and Data Scientists

CBIMK

Scripts simulating the approximation of inverse transformations of probabilistic Markov Kernels for the inference of past states in observable data.

DeepLearningAI-Cambridge-Computer-Vision

Github Repo with code for the Deeplearning.ai Pie & AI Session in Cambridge, led by Kenneth Zhang and Michael Steinberg

DHGOrg

Leveraging DIrected Hypergraphs for Directed Graph Analysis of Repo Commits Anomaly Detection paired with BERT Attention Masking

GraphEmber

Graph Message Passing Construction for LLM Knowledge + Context Graph Link Prediction and Embedding Representations

Normalized-Geometric-Mean-Distance-NGMD

Normalized Geometric Mean Distance (NGMD) - Unique Clustering Metric

StochFlow

a Python library that implements the stochastic interpolant models and algorithms described in the paper "Stochastic Interpolants via Diffusive and Flow-based Processes" by Chen et al.

VisionTransformer

Implementations of the Vision Transformer, and accompanying pre-trained experiments

kennethZhangML/lungSegmentation

Lung Segmentation Program

kennethZhangML/vesselData.github.io

kennethZhangML/lungCTClassifier

Kenneth Zhang - Policython CNN CT Scan Classifier

kennethZhangML/pytorch-rl

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

kennethZhangML/CT_COVID-Scan-Classification-Program

kennethZhangML/Sample-Research-Projects

A Github Repository with a couple samples of Kenneth Zhang's Latest Projects

kennethZhangML/AWS-Data-Exchange-Challenge---Kenneth-Zhang-Project

Kenneth Zhang's AWS Data Exchange Project

kennethZhangML/CT_COVID

kennethZhangML/kennethZhangIgnitionHacksSigma

Code and description for the Ignition Hacks Sigma Problem

kennethZhangML/tf-estimator-tutorials

This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way