Category robotics
Underactuated Robotics
Python implementations of Optimal Control and Optimization algorithms for simulated underactuated systems and walking robots
Learning from Demonstration with Dynamic Movement Primitives
Minimal Python implementation of the Dynamic Movement Primitives (DMPs) framework for the description of demonstrated trajectories with dynamical systems.
Category python
ML 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 Robotics
Python implementations of Optimal Control and Optimization algorithms for simulated underactuated systems and walking robots
Gaussian Processes and Bayesian Optimization
A Python implementation of the Gaussian Processes framework with Bayesian Optimization. Fit noiseless or noisy data and use existing or custom kernels. Bayesian optimization module using existing acquisition functions (μ+kσ,...
Planar robotic arm with arbitrary number of rotary joints
2D robotic arm with arbitrary number of links and rotational joints. Implementation of trajectory planning and kinematic control.
Overused phrases in Suits TV show
Scraping and processing of the TV series Suits transcripts to extract, analyze and visualize most common phrases
Learning from Demonstration with Dynamic Movement Primitives
Minimal Python implementation of the Dynamic Movement Primitives (DMPs) framework for the description of demonstrated trajectories with dynamical systems.
Category visualization
Overused phrases in Suits TV show
Scraping and processing of the TV series Suits transcripts to extract, analyze and visualize most common phrases
Category data science
Overused phrases in Suits TV show
Scraping and processing of the TV series Suits transcripts to extract, analyze and visualize most common phrases
Category machine robotics
Planar robotic arm with arbitrary number of rotary joints
2D robotic arm with arbitrary number of links and rotational joints. Implementation of trajectory planning and kinematic control.
Category machine learning
Neural Network Knowledge Distillation
TensorFlow demonstration of the Knowledge Distillation framework to show how soft labels act as regularizers and a neural network’s knowledge can be transfered to a simpler model
Disjunctive Normal Networks
PyTorch Implementation with sklearn-like API of a Neural Network that constructs a Boolean Function by dividing the feature space with convex polytopes.
ML 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
Gaussian Processes and Bayesian Optimization
A Python implementation of the Gaussian Processes framework with Bayesian Optimization. Fit noiseless or noisy data and use existing or custom kernels. Bayesian optimization module using existing acquisition functions (μ+kσ,...