CNTK
Tulip Indicators
| CNTK | Tulip Indicators | |
|---|---|---|
| 1 | 4 | |
| 17,435 | 802 | |
| 0.0% | 0.7% | |
| 0.0 | 5.2 | |
| about 1 year ago | 3 months ago | |
| C++ | C | |
| GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
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.
CNTK
Tulip Indicators
-
Technical Analysis libraries
TA-lib and pandas-ta have already been mentioned, so just for the sake of alternatives, Tulip indicators
-
IBKR API doesn't provide technical indicators, is there any alternative?
Broker APIs usually don't provide those. You'll want to generate them using a library. The most popular are TA Library (linked by another commenter), TuliPy, and TA-Lib. All easy to use.
-
Here’s the gist of my algorithm. I want to go big with my algorithm and I need some help from you.
I use Tulip Indicators and my codes run on NodeJS and I maintain data on MariaDB. I can of course transform them to any other programming language, if given a chance.
-
C Deep
Tulip Indicators - Library of functions for technical analysis of financial data. LGPL-3.0-or-later
What are some alternatives?
Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
Tulip Cell - TulipCell is an Excel add-in providing 100+ technical analysis indicators.
tensorflow - An Open Source Machine Learning Framework for Everyone
btsk - Behavior Tree Starter Kit
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ANNetGPGPU - A GPU (CUDA) based Artificial Neural Network library
Caffe - Caffe: a fast open framework for deep learning.
AI-Toolbox - A C++ framework for MDPs and POMDPs with Python bindings
Keras - Deep Learning for humans
frugally-deep - A lightweight header-only library for using Keras (TensorFlow) models in C++.
scikit-learn - scikit-learn: machine learning in Python
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.