SciKit-Learn Laboratory VS Pylearn2

Compare SciKit-Learn Laboratory vs Pylearn2 and see what are their differences.

SciKit-Learn Laboratory

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

Pylearn2

Warning: This project does not have any current developer. See bellow. (by lisa-lab)
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SciKit-Learn Laboratory Pylearn2
- 1
552 2,752
0.0% 0.0%
8.7 0.0
about 1 month ago over 2 years ago
Python Python
BSD 1-Clause License BSD 1-Clause License
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.

SciKit-Learn Laboratory

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

We haven't tracked posts mentioning SciKit-Learn Laboratory yet.
Tracking mentions began in Dec 2020.

Pylearn2

Posts with mentions or reviews of Pylearn2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-08.
  • iNeural : Update (8.12.21)
    3 projects | dev.to | 8 Dec 2021
    It is developed by taking inspiration from libraries such as iNeural, FANN, pylearn2, EBLearn, Torch7. Written mostly in C++, iNeural also leverages the power of Python. The biggest reason for its development is that it needs very few dependencies. For this reason, it is expected to be suitable for working in systems with limited system requirements.

What are some alternatives?

When comparing SciKit-Learn Laboratory and Pylearn2 you can also consider the following projects:

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Keras - Deep Learning for humans

seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

tensorflow - An Open Source Machine Learning Framework for Everyone

PyBrain

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

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

gym - A toolkit for developing and comparing reinforcement learning algorithms.