tensorflow VS Keras

Compare tensorflow vs Keras and see what are their differences.

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tensorflow Keras
220 74
179,270 59,979
0.4% 0.5%
10.0 9.9
about 15 hours ago about 14 hours ago
C++ Python
Apache License 2.0 Apache License 2.0
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.


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 2023-11-06.


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 2023-11-28.
  • Keras 3.0
    4 projects | news.ycombinator.com | 28 Nov 2023
    All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467

    You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/

  • Can someone explain how keras code gets into the Tensorflow package?
    2 projects | /r/tensorflow | 24 Jul 2023
    I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?
  • How popular are libraries in each technology
    21 projects | dev.to | 21 Jun 2023
    Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.
  • List of AI-Models
    14 projects | /r/GPT_do_dah | 16 May 2023
    Click to Learn more...
  • I got advice on building ai apps.
    2 projects | /r/learnprogramming | 26 Apr 2023
    Keras documentation: https://keras.io/
  • Mastering Data Science: Top 10 GitHub Repos You Need to Know
    10 projects | dev.to | 24 Apr 2023
    3. Keras Keras is a high-level neural networks API written in Python that’s built on top of TensorFlow. It’s designed to enable fast experimentation with deep learning, allowing you to build and train models with just a few lines of code. If you’re new to deep learning or just want a more user-friendly interface, Keras is the way to go.
  • How to query pandas DataFrames with SQL
    5 projects | dev.to | 1 Feb 2023
    Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more.
  • The Essentials of a Contributor-friendly Open-source Project
    2 projects | dev.to | 18 Jan 2023
    Our trick is to support GitHub Codespaces, which provides a web-based Visual Studio Code IDE. The best thing is you can specify a Dockerfile with all the required dependency software installed. With one click on the repo’s webpage, your contributors are ready to code. Here is our setup for your reference.
    7 projects | dev.to | 16 Jan 2023
    If you’re looking for further resources on running TensorFlow and Keras on a newer MacBook, I recommend checking out this YouTube video: How to Install Keras GPU for Mac M1/M2 with Conda
  • Doing k-fold analysis
    2 projects | /r/tensorflow | 25 Dec 2022
    The thing that pops right into my mind is the following issue: https://github.com/keras-team/keras/issues/13118 People are still reporting memory leaks when calling model.predict and I wouldn't be surprised if model.fit also leaked when called multiple times. Maybe this is a good starting point for your investigation. If this is unrelated, I'm sorry in forward.

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.

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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

LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

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

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

MLflow - Open source platform for the machine learning lifecycle