Pinned Repositories
5MinuteFinance
Interactive Presentations for Financial Education using R/Shiny
a3c_trading
Trading with recurrent actor-critic reinforcement learning
AgeGenderDeepLearning
AILifeWorld
lis version 1 for private
algorithm-trading-webapp
Algorithm Trading web application with Python, Django, PyQt5 and Javascript
Arcade-Learning-Environment
The Arcade Learning Environment (ALE) -- a platform for AI research.
async-deep-rl
A Tensorflow based implementation of "Asynchronous Methods for Deep Reinforcement Learning": https://arxiv.org/abs/1602.01783
async-rl
Replicating "Asynchronous Methods for Deep Reinforcement Learning" (http://arxiv.org/abs/1602.01783)
async_deep_reinforce
Asynchronous Methods for Deep Reinforcement Learning
Mining-the-Social-Web
The official online compendium for Mining the Social Web (O'Reilly, 2011)
dylanthomas's Repositories
dylanthomas/a3c_trading
Trading with recurrent actor-critic reinforcement learning
dylanthomas/async-deep-rl
A Tensorflow based implementation of "Asynchronous Methods for Deep Reinforcement Learning": https://arxiv.org/abs/1602.01783
dylanthomas/CLIP
Contrastive Language-Image Pretraining
dylanthomas/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020
Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020.
dylanthomas/DeepRL-Agents
A set of implementations of Deep Reinforcement Learning Agents using Tensorflow.
dylanthomas/fast-transformers
Pytorch library for fast transformer implementations
dylanthomas/github-cheat-sheet
A list of cool features of Git and GitHub.
dylanthomas/Hello-Generative-Model
PyTorch를 활용한 Generative Model 입문 CAMP (실습자료)
dylanthomas/Horizon
A platform for Applied Reinforcement Learning (Applied RL)
dylanthomas/lambda-networks
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
dylanthomas/level-replay
This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the fact that not all levels are equally useful for agents to learn from during training.
dylanthomas/malmo-challenge
Malmo Collaborative AI Challenge - Team Pig Catcher
dylanthomas/MER
Fork of the GEM project (https://github.com/facebookresearch/GradientEpisodicMemory) including Meta-Experience Replay (MER) methods from the ICLR 2019 paper (https://openreview.net/pdf?id=B1gTShAct7)
dylanthomas/misc
dylanthomas/neural_decomposition
Neural Decomposition Code for Time Series
dylanthomas/neural_prophet
NeuralProphet - a Neural Network based Time-Series model
dylanthomas/OnlineTSA
Online Course of Time Series Analysis
dylanthomas/pbt
Population Based Training (in PyTorch with sqlite3). Status: Unsupported
dylanthomas/predictron
Tensorflow implementation of "The Predictron: End-To-End Learning and Planning"
dylanthomas/pyprobml
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
dylanthomas/pytorch-a3c
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
dylanthomas/pytorch_a3c
dylanthomas/random-network-distillation
dylanthomas/rebel
An algorithm that generalizes the paradigm of self-play reinforcement learning and search to imperfect-information games.
dylanthomas/Reservoir-Computing-framework-for-multivariate-time-series-classification
Library for implementing multivariate time series classifiers based on reservoir computing (echo state network)
dylanthomas/robustopt
dylanthomas/stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
dylanthomas/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.
dylanthomas/SwiftIB
dylanthomas/tleague_projpage