TsetlinMachine
ta-lib-python
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TsetlinMachine | ta-lib-python | |
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3 | 23 | |
449 | 9,009 | |
2.0% | 2.7% | |
3.4 | 7.3 | |
about 1 month ago | about 2 months ago | |
Cython | Cython | |
MIT License | GNU General Public License v3.0 or later |
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.
TsetlinMachine
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[D] Are there unconventional cognition architectures that learn without SGD, weights between neurons, or can only be done on the CPU?
But for unconventional / back to the roots Tsetlin machines is a candidate, https://github.com/cair/TsetlinMachine
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Study reveals that animals cope with environmental complexity by reducing the world into a series of sequential two-choice decisions and use an algorithm to make a decision, a strategy that results in highly effective decision-making no matter how many options there are
Reminds me of Tsetlin machines
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[R] Drop Clause boosts Tsetlin Machine accuracy up to +4% and training speed up to 4x
Hi u/pddpro, there are unfortunately few tutorials available. There are some video resources here: https://github.com/cair/TsetlinMachine#videos and some demos here: https://github.com/cair/pyTsetlinMachine. Currently writing a book: Introduction to Tsetlin Machines. Plan to share drafts of the chapters here as I proceed, including tutorials.
ta-lib-python
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Why is my RSI coming up incorrect?
One such excellent Python library is TA-Lib. (https://github.com/TA-Lib/ta-lib-python)
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Technical Analysis libraries
Have you looked TA-Lib?
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Crypto Data Bot using Python, Binance WebSockets and PostgreSQL DB
TA-Lib
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Why Economists should embrace Data Science
Dev here. I've wanted to get into doing this for as long as I can remember. Back in 2018 I got a half start at it, pulling in Binance candle data for all intervals with python and then running them all through every TA function of ta-lib to generate corresponding indicators. I intended to take it that next step further into picking up ML, and wanted to write a script that would pair every permutation of indicator looking for combinations that improve certainty for price direction changes (the certainty of BOLL + RSI was going to be used as my baseline for a known semi-reliable combo). I would really love to circle back someday to finishing that up, and then start sucking in candle data from as many markets as I could afford the AWS services for lol. That's my dream dashboard.
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How are these guys doing automated trend analysis like finding falling wedges, bullish pennants or bull flag?
Not sure what they are using specifically, but ta-lib has candle pattern matching.
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Relative Strength in Python; am I coding it right?
Just use TA-Lib https://mrjbq7.github.io/ta-lib/
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looking for a python lib
Doesn't seem like an official mirror but if you're curious what the code looks like, including the python/C bindings, here it is: https://github.com/mrjbq7/ta-lib
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Calculating EMA200 from Binance API?
I use talib https://mrjbq7.github.io/ta-lib/ and it accurately mirrors binance
- Baby python advice
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How to install TA-lib in a linux machine w/o root?
This from a closed issue.
What are some alternatives?
fim - FIM is an Open Source Host-based file integrity monitoring tool that performs file system analysis, file integrity checking, real time alerting and provides Audit daemon data.
pandas-ta - Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
pyTsetlinMachine - Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
ta - Technical Analysis Library using Pandas and Numpy
GODM
finta - Common financial technical indicators implemented in Pandas.
deep-learning-drizzle - Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
tmu - Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
trading-utils - Collection of scripts and utilities for stock market analysis, strategies etc
Alpaca-API - The Alpaca API is a developer interface for trading operations and market data reception through the Alpaca platform.