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deep-q-trading-cryptocurrencies

Master annual project that aims to make an agent able to trade on a cryptocurrency market and make benefits.

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep-reinforcement-learning-for-automated-stock-trading-ensemble-strategy-icaif-2020

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020.

deep-reinforcement-learning-for-automated-stock-trading-strategy

Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock market. In this paper, we propose a deep ensemble reinforcement learning scheme that automatically learns a stock trading strategy by maximizing investment return. We train a deep reinforcement learning agent and obtain an ensemble trading strategy using the three actor-critic based algorithms: Proximal Policy Optimization (PPO), Advantage Actor Critic (A2C), and Deep Deterministic Policy Gradient (DDPG). The ensemble strategy inherits and integrates the best features of the three algorithms, thereby robustly adjusting to different market conditions. In order to avoid the large memory consumption in training networks with continuous action space, we employ a load-on-demand approach for processing very large data. We test our algorithms on the 30 Dow Jones stocks which have adequate liquidity. The performance of the trading agent with different reinforcement learning algorithms is evaluated and compared with both the Dow Jones Industrial Average index and the traditional min-variance portfolio allocation strategy. The proposed deep ensemble scheme is shown to outperform the three individual algorithms and the two baselines in terms of the risk-adjusted return measured by the Sharpe ratio.

deep-reinforcement-learning-for-hedging

Hedging unsing Deep Reinforcement Learning and Deep Learning

deep-reinforcement-stock-trading

A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.

deep-rl-project---maximize-total-profits-earned-by-cab-driver

The goal of this project is to build an RL-based algorithm that can help cab drivers maximize their profits by improving their decision-making process on the field. Taking long-term profit as the goal, a method is proposed based on reinforcement learning to optimize taxi driving strategies for profit maximization. This optimization problem is formulated as a Markov Decision Process i.e. MDP.

deep-rl-trading

playing idealized trading games with deep reinforcement learning

deep-text-recognition-benchmark

Text recognition (optical character recognition) with deep learning methods.

deep-trading-agent

Deep Reinforcement Learning based Trading Agent for Bitcoin

deep_fundamental_factors

Source code for Deep Fundamental Factor Models, https://arxiv.org/abs/1903.07677

deep_rl_trader

Trading Environment(OpenAI Gym) + DDQN (Keras-RL)

deepai

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

deeperspeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

deeplob

deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

deeplob-model-implementation-project

This repo contains some codes and outputs of my implementation of DeepLOB model.

deeplob-trading_app

deeplob_pytorch

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deepspeech-german

Automatic Speech Recognition (ASR) - German

deepspeech-german-1

Scripts for training Mozilla's DeepSpeech using german speech data

deepswarm

Neural Architecture Search Powered by Swarm Intelligence 🐜

deeptrader

deepwordbug

CodeBase for Paper: "Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers", / Interactive Demo @

deepwto

Prepares a public dataset that pairs citable WTO legal articles with a textual description of government measure

degiro-portfolio-manager

Simple web tool to crunches Degiro account statement reports into per position PL, commissions, and taxes information

deliveryguy

Wojak quits his job at McDonalds and becomes a Takeaway driver.

delta-divergence-bot

This bot will aim to identify delta divergence through binance.

demo-python-trading-bot

Demo bot for scalping strategy on Waves based DEXes (waves.exchange)