CNTK VS Tulip Indicators

Compare CNTK vs Tulip Indicators and see what are their differences.

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CNTK Tulip Indicators
1 4
17,435 802
0.0% 1.7%
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
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.

CNTK

Posts with mentions or reviews of CNTK. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-20.

Tulip Indicators

Posts with mentions or reviews of Tulip Indicators. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-23.

What are some alternatives?

When comparing CNTK and Tulip Indicators you can also consider the following projects:

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 - 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.