tensorflow VS Keras

Compare tensorflow vs Keras and see what are their differences.

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tensorflow Keras
119 32
162,156 53,748
0.7% 0.7%
10.0 9.8
about 3 hours ago about 3 hours ago
C++ 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.

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.

Keras

Posts with mentions or reviews of Keras. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-11.

What are some alternatives?

When comparing tensorflow and Keras 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.

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

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

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

TFLearn - Deep learning library featuring a higher-level API for TensorFlow.

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

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