Pinned Repositories
densityClust
Clustering by fast search and find of density peaks
Dynamics-and-Control
Jupyter notebooks for Dynamics and Control
edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
keras
Deep Learning for humans
machine_learning
Machine Learning 2016/2017 - MSc Artificial Intelligence @ UvA
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
pyro
Deep universal probabilistic programming with Python and PyTorch
Python-for-Signal-Processing
Notebooks for "Python for Signal Processing" book
FC-31's Repositories
FC-31/densityClust
Clustering by fast search and find of density peaks
FC-31/Dynamics-and-Control
Jupyter notebooks for Dynamics and Control
FC-31/edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
FC-31/filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
FC-31/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
FC-31/keras
Deep Learning for humans
FC-31/machine_learning
Machine Learning 2016/2017 - MSc Artificial Intelligence @ UvA
FC-31/pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
FC-31/pyro
Deep universal probabilistic programming with Python and PyTorch
FC-31/Python-for-Signal-Processing
Notebooks for "Python for Signal Processing" book
FC-31/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
FC-31/scikit-sos
Stochastic Outlier Selection
FC-31/SDETools
Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations
FC-31/Skogestad-Python
Python code for "Multivariable Feedback Control"
FC-31/spark-stochastic-outlier-selection
FC-31/tensorboard
TensorFlow's Visualization Toolkit
FC-31/tensorflow
Computation using data flow graphs for scalable machine learning
FC-31/vankampen-stochastic
Exercises and notes for N.G. Van Kampen's Stochastic Processes in Physics and Chemistry