Pylearn2
SciKit-Learn Laboratory
Our great sponsors
Pylearn2 | SciKit-Learn Laboratory | |
---|---|---|
1 | - | |
2,752 | 552 | |
0.0% | 0.0% | |
0.0 | 8.7 | |
over 2 years ago | about 2 months ago | |
Python | Python | |
BSD 1-Clause License | GNU General Public License v3.0 or later |
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.
Pylearn2
-
iNeural : Update (8.12.21)
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.
SciKit-Learn Laboratory
We haven't tracked posts mentioning SciKit-Learn Laboratory yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
Keras - Deep Learning for humans
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tensorflow - An Open Source Machine Learning Framework for Everyone
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
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
gym - A toolkit for developing and comparing reinforcement learning algorithms.
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)