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Machine Learning & Data Science · head to head

Keras vs Orange

Keras logo

Keras

Machine Learning & Data Science

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite
Orange logo

Orange

Machine Learning & Data Science

Data mining and visualization toolkit

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
  • They diverge on capability: Keras covers Sequential and Functional API, Orange covers Visual programming.

Where they differ

Only the attributes on which Keras and Orange actually diverge.

Attributes where Keras and Orange differ
AttributeKerasOrange
PlatformsPython, Google Colab, JupyterLinux, Mac, Windows
Founded20151996

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • TensorFlow
  • JAX
  • PyTorch

Only in Orange

  • Visual programming
  • Data visualization
  • Machine learning
  • Text mining
  • Bioinformatics
  • Python
  • scikit-learn
  • PyQt

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

The jobs each tool is most often brought in to do.

Keras

  • Machine learningnot Orange
  • Data analysisnot Orange
  • Model trainingnot Orange
  • Predictive analyticsnot Orange

Orange

  • Visual programming for data mining and machine learning workflowsnot Keras
  • Teaching data science without writing codenot Keras
  • Exploratory data visualisation and clustering on tabular datanot Keras

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Keras

  • Limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • Error messages can be vague and unhelpful, making debugging challenging
  • Smaller ecosystem and fewer pre-trained models than TensorFlow or PyTorch

Orange

  • Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
  • The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
  • Orange add-ons may carry additional licensing requirements set in their own licence files
  • Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
  • The software is distributed without any warranty of merchantability or fitness for a particular purpose

Pricing, plan by plan

Keras

Free
  • Open SourceFree
    • High-level API
    • Pre-built layers
    • Model serialization

Orange

Free
  • Open SourceFree
    • Visual programming
    • Machine learning
    • Data visualization

Which should you pick?

Choose Keras if

  • You need sequential and functional api.
  • You want to start without paying.
  • You work on Python, Google Colab, Jupyter.
  • You also want pre-built neural network layers.
Keras review

Choose Orange if

  • You need visual programming.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data visualization.
Orange review

Questions people ask

Is Keras or Orange better?
Neither clearly leads. Keras starts at Free and Orange at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Orange?
Keras starts at Free and Orange at Free.
Does Keras or Orange run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Orange runs on Linux, Mac, Windows.
Can I use Keras for free?
Both have a free tier, so you can try either at no cost before committing.
What is Keras best used for?
Keras is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Orange is typically brought in for.
What can Keras do that Orange cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Orange covers Visual programming, Data visualization, Machine learning, Text mining. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

Keras: What is Keras?

Keras is a high-level deep learning API built on top of TensorFlow that simplifies building and training neural networks. Keras 3 supports multiple backends including TensorFlow, PyTorch, and JAX, making it backend-agnostic.

Source
Keras: What model architectures does Keras support?

Keras supports the Sequential model for linear stacks of layers, the Functional API for arbitrary graph architectures, and model subclassing for custom implementations. All approaches provide access to layers, optimizers, metrics, and callbacks.

Source
Keras: Can Keras models run on TPUs and GPUs?

Yes, Keras models can run on TPU Pods or large GPU clusters, be exported to run in browsers or on mobile devices, and be served via web APIs.

Source
Keras: Does Keras offer pre-trained models?

Yes, Keras provides pre-trained models through KerasHub and Keras Applications for common deep learning tasks like image classification, object detection, and NLP.

Source
Keras: Who should use Keras?

Keras is ideal for beginners and rapid prototyping due to its simplicity and user-friendly interface. Advanced users and production deployments may benefit more from lower-level frameworks like TensorFlow or PyTorch for greater customization.

Source
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