eycab Goto Github PK

lime

Lime: Explaining the predictions of any machine learning classifier

list_of_recommender_systems

A List of Recommender Systems and Resources

loss-landscape

Code for visualizing the loss landscape of neural nets

lscp

Supplementary material for SDM paper "LSCP: Locally Selective Combination in Parallel Outlier Ensembles"

lstm-anomaly-detect

Example code for neural-network-based anomaly detection of time-series data (uses LSTM)

lstm-attention

LSTM-Attention

lstm-fcn

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification

lstm-sentiment-analysis

Sentiment Analysis with LSTMs in Tensorflow

lstmvis

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

luminol

Anomaly Detection and Correlation library

machina

Deep Reinforcement Learning framework

machine-learning

:earth_americas: machine learning tutorials (mainly in Python3)

machine-learning-mindmap

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

magent

A Platform for Many-agent Reinforcement Learning

markov_clustering

markov clustering in python

marl-papers

Paper list of multi-agent reinforcement learning (MARL)

maxlives-projects

mc_gradients

mcfly

A deep learning tool for time series classification

mcfly-tutorial

tutorial for mcfly repository

mcmc

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

mcmc-denoiser

Gibbs sampling MCMC image denoiser

mcmc_fnn_timeseries

Bayesian Neural Network for Time Series Prediction

mcmcplotlib

Python package to plot MCMC samples

memory-efficient-attention-pytorch

Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"

meta-learning

Meta Reinforcement Learning Experiments

meta-learning-papers

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning