technicalindicators VS Deep_Learning_Machine_Learning_Stock

Compare technicalindicators vs Deep_Learning_Machine_Learning_Stock and see what are their differences.

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technicalindicators Deep_Learning_Machine_Learning_Stock
1 48
2,097 1,155
- -
0.0 6.1
over 1 year ago 3 months ago
JavaScript Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

technicalindicators

Posts with mentions or reviews of technicalindicators. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing technicalindicators and Deep_Learning_Machine_Learning_Stock you can also consider the following projects:

bitcoin-chart-cli - Bitcoin chart for the terminal as command line util

tsfresh - Automatic extraction of relevant features from time series:

pandas-ta - Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators

bulbea - :boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

StockSocket - Get Real-Time Stock Data

FinanceDataReader - Financial data reader [Moved to: https://github.com/FinanceData/FinanceDataReader]

TradingGym - Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.

deltapy - DeltaPy - Tabular Data Augmentation (by @firmai)

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