optapy VS TFLearn

Compare optapy vs TFLearn and see what are their differences.

optapy

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems. (by optapy)
Machine Learning Python Python3 Artificial intelligence Metaheuristics local-search simulated-annealing tabu-search vehicle-routing-problem employee-rostering task-assignment traveling-salesman-problem np-hard np-complete mathematical-optimization
Source Code
optapy.org
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TFLearn

Deep learning library featuring a higher-level API for TensorFlow. (by tflearn)
Machine Learning Tflearn Tensorflow neural-network Deep Learning Data Science
Source Code
tflearn.org
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optapy TFLearn
2 2
259 9,605
0.8% 0.0%
5.5 0.0
7 months ago 5 months ago
Java Python
Apache License 2.0 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.

optapy

Posts with mentions or reviews of optapy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-06.

TFLearn

Posts with mentions or reviews of TFLearn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-14.
  • Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)
    8 projects | dev.to | 14 Aug 2022
    TFLearn – Deep learning library featuring a higher-level API for TensorFlow
  • Base ball
    1 project | dev.to | 20 Mar 2021
    Both the teams in a game are given their individual ID values and are made into vectors. Relevant data like the home and away team, home runs, RBI’s, and walk’s are all taken into account and passed through layers. There’s no need to reinvent the wheel here, there's a multitude of libraries that enable a coder to implement machine learning theories efficiently. In this case we will be using a library called TFlearn, documentation available from http://tflearn.org. The program will output the home and away teams as well as their respective score predictions.

What are some alternatives?

When comparing optapy and TFLearn you can also consider the following projects:

or-tools - Google's Operations Research tools:

Keras - Deep Learning for humans

scikit-learn - scikit-learn: machine learning in Python

tensorflow - An Open Source Machine Learning Framework for Everyone

VeRyPy - A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.

skflow - Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

SciKit-Learn Laboratory - SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

NuPIC - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

tfgraphviz - A visualization tool to show a TensorFlow's graph like TensorBoard

optapy vs or-tools TFLearn vs Keras optapy vs scikit-learn TFLearn vs tensorflow optapy vs tensorflow TFLearn vs scikit-learn optapy vs VeRyPy TFLearn vs skflow optapy vs SciKit-Learn Laboratory TFLearn vs NuPIC optapy vs spaCy TFLearn vs tfgraphviz