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reinforcement-learning-in-portfolio-management-

This project implements the two deep reinforcement learning algorithms on portfolio management

reinforcement_learning_for_stock_prediction

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

relationprediction

Implementation of R-GCNs for Relational Link Prediction

retail-sales-forecasting-with-meta-learning

riskfolio-lib

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

rl-tutorial-jnrr19

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

rlmc

robo_advisor

Deep Reinforcement Learning Robot Advisor

rstg

runoob-tit-test

sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker

scimai-gym

A Python library for addressing the Supply Chain Inventory Management problem through Deep Reinforcement Learning algorithms.

sdpdmod

Spatial Dynamic Panel Data models

short-term-electrical-load-forecast

Short-term load forecasting

sieg_ogb

smc_electricity_forecast

Projet ENSAE - Modèles à chaîne de Markov cachée et méthodes de Monte Carlo séquentielles - Antoine Grelety, Samir Tanfous, Zakarya Ali

social-network-analysis-in-r

Social-Network-Analysis-in-R

soft2017fall-business-intelligence-teaching-material

This repository contains lecture notes and exercises for the Business Intelligence elective course at Copenhagen Business Academy.

solar-energy-analytics

A set of data-driven solutions for solar energy challenges.

solve-air-air-pollution-forecasting-using-deep-attentive-sequence-learning

First step towards solving a real-life problem - air pollution forecasting in Delhi, using deep learning

spektral

Graph Neural Networks with Keras and Tensorflow 2.

spring-2015-homeworks

st

stgcn_ijcai-18

Spatio-Temporal Graph Convolutional Networks

stock-volatility-forecasting

The extra value of online investor sentiment measures on forecasting stock return volatility: a large-scale longitudinal evaluation based on Chinese stock market

stockprediction

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stockx-predictive-modeling

This repository is dedicated to the machine learning analysis on StockX prices. Blog 👉

superset

Apache Superset is a Data Visualization and Data Exploration Platform

supplychainv0_gym

Reinforcement Learning for Optimal inventory policy