Deep_Learning_Machine_Learning_Stock
FinanceDataReader
| Deep_Learning_Machine_Learning_Stock | FinanceDataReader | |
|---|---|---|
| 48 | 17 | |
| 1,149 | 950 | |
| - | - | |
| 6.1 | 0.0 | |
| 2 months ago | 12 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Deep_Learning_Machine_Learning_Stock
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:1017.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:924.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:792.0
- Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:729.0
- Deep-Learning-Machine-Learning-Stock: curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may b
FinanceDataReader
What are some alternatives?
tsfresh - Automatic extraction of relevant features from time series:
investpy - Financial Data Extraction from Investing.com with Python
bulbea - :boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
core-js - Standard Library
TradingGym - Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
superstonk - Follow your favourite stock right in the terminal window
deltapy - DeltaPy - Tabular Data Augmentation (by @firmai)
FinanceDataReader - Financial data reader [Moved to: https://github.com/financedata-org/FinanceDataReader]
DataScienceProjects
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
Algo-Trading - This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!
Astock - Astock