Tulip Indicators VS Veles

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

Tulip Indicators

Technical Analysis Indicator Function Library in C (by TulipCharts)

Veles

Distributed machine learning platform (by Samsung)
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Tulip Indicators Veles
4 -
802 903
0.7% 0.1%
5.2 3.4
3 months ago 6 months ago
C C++
GNU Lesser General Public License v3.0 only GNU General Public License v3.0 or later
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.

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.

Veles

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

We haven't tracked posts mentioning Veles yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

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

Tulip Cell - TulipCell is an Excel add-in providing 100+ technical analysis indicators.

tiny-cnn - header only, dependency-free deep learning framework in C++14

btsk - Behavior Tree Starter Kit

tensorflow - An Open Source Machine Learning Framework for Everyone

CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

AI-Toolbox - A C++ framework for MDPs and POMDPs with Python bindings

ANNetGPGPU - A GPU (CUDA) based Artificial Neural Network library

frugally-deep - Header-only library for using Keras (TensorFlow) models in C++.

BayesOpt - BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.