H2O vs Keras vs TensorFlow

Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

H2O
H2O

51
49
+ 1
0
Keras
Keras

434
352
+ 1
11
TensorFlow
TensorFlow

1.3K
1.2K
+ 1
62

What is H2O?

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

What is Keras?

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

What is TensorFlow?

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Why do developers choose H2O?
Why do developers choose Keras?
Why do developers choose TensorFlow?
    Be the first to leave a pro

    Sign up to add, upvote and see more prosMake informed product decisions

      Be the first to leave a con
      What companies use H2O?
      What companies use Keras?
      What companies use TensorFlow?

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with H2O?
      What tools integrate with Keras?
      What tools integrate with TensorFlow?
        No integrations found

        Sign up to get full access to all the tool integrationsMake informed product decisions

        What are some alternatives to H2O, Keras, and TensorFlow?
        scikit-learn
        scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
        PyTorch
        PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
        ML Kit
        ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
        CUDA
        A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
        TensorFlow.js
        Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
        See all alternatives
        Decisions about H2O, Keras, and TensorFlow
        Conor Myhrvold
        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber · | 6 upvotes · 549.8K views
        atUber TechnologiesUber Technologies
        TensorFlow
        TensorFlow
        Keras
        Keras
        PyTorch
        PyTorch

        Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

        At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

        TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details—for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA’s CUDA toolkit.

        Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo’s deep learning toolkit which makes it easier to start—and speed up—distributed deep learning projects with TensorFlow:

        https://eng.uber.com/horovod/

        (Direct GitHub repo: https://github.com/uber/horovod)

        See more
        Interest over time
        Reviews of H2O, Keras, and TensorFlow
        No reviews found
        How developers use H2O, Keras, and TensorFlow
        Avatar of Eliana Abraham
        Eliana Abraham uses TensorFlowTensorFlow

        Machine Learning in EECS 445

        Avatar of Taylor Host
        Taylor Host uses TensorFlowTensorFlow

        Pilot integration for retraining.

        How much does H2O cost?
        How much does Keras cost?
        How much does TensorFlow cost?
        Pricing unavailable
        Pricing unavailable
        Pricing unavailable
        News about H2O
        More news
        News about Keras
        More news