physhik Goto Github PK

3dcnn

acapellabot

Acapella Extraction with a ConvNet

bayesian-modelling-in-python

A python tutorial on bayesian modeling techniques (PyMC3)

began-tensorflow

Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

cnn_music

A CNN for music genre classification and TSC in general

covid19-sir

COVID-19 SIR model estimation

data-science-from-scratch

code for Data Science From Scratch book

dcgan

A Tensorflow Implementation of "Deep Convolutional Generative Adversarial Networks" - (EASY to READ)

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deepmind-atari-deep-q-learner

The original code from the DeepMind article + my tweaks

doing_bayesian_data_analysis

Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke

dqn

This is a very basic DQN implementation, which uses OpenAI's gym environment and Keras/Theano neural networks.

dynamic-tensorflow-tutorial

Tensorflow tutorial of building different dynamic recurrent neural network

ecg-mit-bih

ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

genrexpose

Automated music genre classification using machine learning

gtzan.keras

[REPO] Music Genre classification on GTZAN dataset using CNNs

holy-edge

Holistically-Nested Edge Detection

kaggle-ensemble-guide

Code for the Kaggle Ensembling Guide Article on MLWave

keras-flask-deploy-webapp

:smiley_cat: Pretty&simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.

keras_extensions

A collection of small extensions to Keras (RBM, momentum schedule, ..)

mlclass

Python code for Machine Learning course from Coursera

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

parallel_ml_tutorial

Tutorial on scikit-learn and IPython for parallel machine learning

pathintegral-qmc

A path-integral quantum Monte Carlo code for simulating quantum annealing with arbitrary Ising Hamiltonians.

physhik.github.io

pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

progressive-growing-torch

Torch implementation of "PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION"

progressive_growing_of_gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation

pymc

PyMC: Bayesian Stochastic Modelling in Python (for PyMC3: https://github.com/pymc-devs/pymc3)

pymc3

Probabilistic Programming in Python. Uses Theano as a backend, supports NUTS and ADVI.