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reinforcement_learning_demos

Demonstrations of Reinforcement Learning algorithms, as part of the COMP767 Reinforcement Learning course at McGill University

reinforcement_learning_experiments

reinforcement_learning_for_stock_prediction

This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube

reinspect

End to end detection in crowded scenes

related-skills

Data-Mine Related Tech Skills

relation-network

Tensorflow Implementation of Relation Networks for the bAbI QA Task, detailed in "A Simple Neural Network Module for Relational Reasoning," [https://arxiv.org/abs/1706.01427] by Santoro et. al.

relation-network-tensorflow

Tensorflow implementations of Relational Networks and a VQA dataset named Sort-of-CLEVR proposed by DeepMind.

relational-gcn

Keras-based implementation of Relational Graph Convolutional Networks

relational_learners

A library of relational learning algorithms.

relationprediction

Implementation of R-GCNs for Relational Link Prediction

relative_depth

Code for the NIPS 2016 paper

relax

Optimizing control variates for black-box gradient estimation

relevance-prop

A numpy implementation of pixel-wise relevance propagation by Sebastian Bach et al.

relevance-ranking-using-latent-semantic-indexing--from-scratch-

Latent Semantic Analysis Introduction: An information retrieval technique patented in 1988. In the context of its application to information retrieval, it is sometimes called Latent Semantic Indexing (LSI). LSI allows a search engine to determine what a page is about outside of specifically matching search query text. It looks at “Themes” instead of “Keywords”. Linear Algebra techniques used in the project: Singular Value Decomposition, Cosine Similarity, Matrix properties. Dataset: “Sci.space” news group from 20 news groups dataset, available in the Scikit-Learn library. It contains 400 news articles related to space. SVD (Singular Value Decomposition): SVD is a matrix decomposition algorithm, it decomposes a matrix into 3 matrices which are a set to transformations. Decomposition leads to an orthogonal matrix U, Diagonal matrix S and a Diagonal Matrix V. This is the best possible transformation of a matrix. In this decomposition method we are looking for a set of orthonormal basis in the row space that when multiplied by the original matrix goes to an orthonormal basis in the column space.Av1 = σ1u1  Av2 = σ2u2 

reliability-modeling-for-stock-comments

Reliability Modeling for Stock Comment

relpro

Relationship Profiling over Content-Rich Diffusion Networks

remi

Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.

remote-pip

Install pip packages in remote hosts

remote_storage

Connecting a Binder repository with data stored remotely.

remotespawner

Remote Spawner class for JupyterHub to spawn IPython notebooks and a remote server and tunnel the port via SSH

remove-before-flight

Remove before flight: Analysing flight safety data with Python - PyData Madrid 2016 talk

renamer

Rename XP output files

renkotrading

Simple algorithm inspired on Renko charts applied to cryptocurrency trading

repeatea

一定価格で繰り返し取引するEA

repenrich

RepEnrich is a method to estimate repetitive element enrichment using high-throughput sequencing data.

replay_classification

State space models for categorization of replay content from multiunit spiking activity. Deng et al. 2016

replay_identification

A semi-latent state-space model that combines movement, LFP, and ensemble spiking information to identify periods of replay and decode its content in real time. Long Tao et al., unpublished.

replicate_google_trends

Replication of "Quantifying Trading Behavior in Financial Markets Using Google Trends" by Preis et al 2013

replicating-deepmind

Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind

replicating_strategy

A dynamic strategy that replicates the payoff of a derivative described as a stochastic process