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ml-finance's Introduction

๐Ÿ’ฐ Finance related machine learning examples

Because I've seen many examples on Github that are either incomplete, unreliable, poorly documented or have errors.

All examples use Jupyter Notebook so you can view the example on github with plots before cloning the repo. Jupyter Notebooks also make it easier to run and debug.

Pull requests and issues welcome.

๐Ÿ“’ How to run

Open the the Jupyter Notebook from each example and follow the steps.

๐Ÿ“ˆ Data

All data is included in the examples or is from financial-data

๐Ÿ“– Examples

Example 0: Deep Q Learning with 3 stocks

Location: 0-deep-q-learning-3-stocks

Example 1: Deep Q Learning simulated price data

Location: 1-deep-q-learning-simulated

Example 2: LSTM model with FOREX data

Location: 2-lstm-forex

Example 3: LSTM model with simulated price data

Location: 3-lstm-simulated

Example 4: Time Series Forecasting with LSTM

Location: 4-time-series-forcasting-lstm

Example 5: PPO2 and MLP trading AAPL stock

Location: 5-ppo2-ml-appl

Example 6: Random Forest Classifier to prediction direction of DAX 30

Location: 6-random-forest-dax30

Example 7: Random Forest Classifier with simulated price data

Location: 7-random-forest-simulated

Example 8: Deep Q Learning with FOREX data

Location: 8-deep-q-forex

Example 9: Deep Q Learning with FOREX more data and technical indicators

Location: 9-deep-q-forex-more-data

Example 10: Deep Q Learning with FOREX fewer technical indicators

Location: 10-deep-q-forex-variations

Example 11: Deep RL Trader (Duel DQN) Implemented using Keras-RL

Location: 11-deep-rl-trader

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