tsitsimis

dmpling

Dynamic Movement Primitives in Python

constrainedlr

Drop-in replacement of sklearn's Linear Regression with coefficients constraints

tinyshap

Python package providing a minimal implementation of the SHAP algorithm using the Kernel method

from-scratch

Machine Learning implementations from scratch. Using minimal dependencies this collection intends to cover fundamental machine learning algorithms: from linear regression to neural networks

underactuated

Python implementations of Optimal Control and Optimization algorithms for simulated underactuated systems and walking robots

8R-redundant-robotic-arm

8R redundant robotic arm with obstacle avoidance

neural-network-distillation

Simple demonstration of the Knowledge Distillation framework with neural networks

disjunctive-normal-networks

PyTorch implementation of Disjunctive Normal Networks

planar-robot

Basic planar robotic arm with arbitrary number of rotary joints

suits-overused-phrases

Scraping and processing of the TV series Suits transcript to extract most common phrases

gau-pro

Gaussian Processes and Bayesian Optimization implemeted in Python

lazy-stack

Automatically create SQL Alchemy models from Great Expectations suites

novel

Anomaly detection with One-Class SVM in Python from scratch

robot-handover

A controller for the humanoid robot NAO for interactive human-to-robot object handovers

dash-flow-diagrams

GP4ML

Gaussian Processes for Machine Learning

tsitsimis.github.io

https://tsitsimis.github.io/