tensorflow VS scikit-learn

Compare tensorflow vs scikit-learn and see what are their differences.

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tensorflow scikit-learn
119 30
162,156 48,549
0.8% 1.0%
10.0 9.9
1 day ago 6 days ago
C++ Python
Apache License 2.0 OSI Approved
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.

tensorflow

Posts with mentions or reviews of tensorflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-12.

scikit-learn

Posts with mentions or reviews of scikit-learn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-17.

What are some alternatives?

When comparing tensorflow and scikit-learn you can also consider the following projects:

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)

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

Surprise - A Python scikit for building and analyzing recommender systems

PyBrain

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

gensim - Topic Modelling for Humans

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration