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Deep Reinforcement Learning to Play 2048 (with Keras)
dqn-2048's Introduction
- Languages: Python (main focus), R, MATLAB, Bash
- OS/Dev/Misc. Tools/Software: Linux, Git, Poetry, Docker, Excel/VBA
- Database/Datastore/API/IO: MongoDB, PyMongo, Parquet, HDF5, RESTful APIs, asyncio, aiohttp
- Data Science/Scientific Computing Stack: Pandas, Numpy, Scipy, Scikit-Learn, StatsModels, Optuna
- Parallel/Distributed/Cloud/GPU Computing: Google Cloud, Ray, Dask.distributed, Dask DataFrame, ML training/hyperparam optimization on Multi-CPU/Multi-GPU clusters (NVIDIA RAPIDS: cuDF/Dask-cuDF, Dask-CUDA, cuML/Dask-cuML)
- Data Analytics Apps/Dashboards/Front-end: Plotly Dash
- Quantitative Finance: Quantlib
Trading Strategies & Asset Classes/Products:
- (Black-Box/Machine Learning/Deep Learning) Statistical Arbitrage/Systematic Macro on Futures (Commodities/Energy/Metals/Stock Indices), Cash Equities, Forex
- Systematic Volatility (Volatility Risk-Premia/Volatility Arbitrage) on ETF Stock Index Options, Credit Index Options
- Traded in personal capacity (macro trading/investing): Futures, Futures Options, ETFs, ETF Options, Forex
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dqn-2048's Issues
i just try dqn , and don't use any method to get the future status, but i think it's hard to get 1024 or 2048,it may stop at 512.