Deadmoustache

Deadmoustache's Stars

• mml-book/mml-book.github.io

  Companion webpage to the book "Mathematics For Machine Learning"

  Language:Jupyter Notebook13.2k4797682.4k

• hongleizhang/RSPapers

  RSTutorials: A Curated List of Must-read Papers on Recommender System.

  6.2k33441.3k

• JWarmenhoven/ISLR-python

  An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

  Language:Jupyter Notebook4.2k205152.4k

• justmarkham/scikit-learn-videos

  Jupyter notebooks from the scikit-learn video series

  Language:Jupyter Notebook3.7k348112.5k

• robi56/Deep-Learning-for-Recommendation-Systems

  This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

  2.8k2031703

• oxwhirl/pymarl

  Python Multi-Agent Reinforcement Learning framework

  Language:Python1.9k29130384

• FenTechSolutions/CausalDiscoveryToolbox

  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

  Language:Python1.1k37143199

• miguelgfierro/ai_projects

  AI projects

  Language:Jupyter Notebook80343101181

• WillKoehrsen/wikipedia-data-science

  Working with and analyzing Wikipedia Data

  Language:Jupyter Notebook692234288

• DOsinga/deep_learning_cookbook

  Deep Learning Cookbox

  Language:Jupyter Notebook6883766337

• caserec/CaseRecommender

  Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems

  Language:Python484222691

• stared/interactive-machine-learning-list

  A collaborative list of interactive Machine Learning, Deep Learning and Statistics websites

  Language:JavaScript43230742

• fooof-tools/fooof

  Parameterizing neural power spectra into periodic & aperiodic components.

  Language:Python3612819697

• PyMVPA/PyMVPA

  MultiVariate Pattern Analysis in Python

  Language:Python31236280135

• a-martyn/ISL-python

  Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

  Language:Jupyter Notebook30581117

• neurodsp-tools/neurodsp

  Digital signal processing for neural time series.

  Language:Python2821712261

• gkamradt/Lessons-Learned-Data-Science-Interviews

  Lessons learned the hard way through over 30+ data science interviews

  225150112

• PhABC/neuroSummerSchools

  List of summer schools in neuroscience and related fields

  Language:Python21548537

• cosanlab/nltools

  Python toolbox for analyzing imaging data

  Language:Python1221028844

• ramhiser/activelearning

  Active Learning in R

  Language:R4591912

• pzeidman/dcm-peb-example

  Tutorial papers and dataset illustrating group connectivity analysis with DCM and PEB

  Language:TeX412117

• jeroenvanbaar/MoralStrategiesFMRI

  Code accompanying the manuscript: Van Baar, J., Chang, L., & Sanfey, A.G. (2019). The computational and neural substrates of moral strategies in social decision-making. Nature Communications.

  Language:Jupyter Notebook263012

• voytekresearch/pacpy

  Calculate phase-amplitude coupling in Python (and Matlab).

  Language:Jupyter Notebook2493512

• bettytijms/Single_Subject_Grey_Matter_Networks

  Matlab scripts that extract single subject grey matter networks from grey matter segmented T1 weighted images

  Language:MATLAB14107

• CyclotronResearchCentre/SPM_ClusterSizeThreshold

  SPM Cluster Size Threshold estimation

  Language:MATLAB13711

• shanest/quantifier-rnn-learning

  Accompanies the paper "Learnability and Semantic Universals" ; trains recurrent neural networks to learn to verify sentences with quantifiers in order to explain semantic universals

  Language:Python114010

• bartleyneuro/OctaveMVPA

  An All-in-One Princeton MVPA, AFNI-for-MATLAB, and SPM Distro: All Converted for Use in Octave

  Language:MATLAB6203

• kuixu/MiniBatchSVM

  Mini-batch SVM / Logistic Regresion, Online learning for large scale data.

  Language:Python6201

• sentimos/svm

  Tensorflow implementation of Andrew Ng SVM examples from Machine Learning course

  Language:Jupyter Notebook6114

• kwimac/pw_pwzn_z2019

  Language:HTML32021