Software · head to head
Azure Machine Learning vs Keras
Azure Machine Learning
Software
Enterprise-grade machine learning service
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Azure Machine Learning requires knowledge of Azure ecosystem and integration with other Azure services; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
- They diverge on capability: Azure Machine Learning covers Automated ML, Keras covers Sequential and Functional API.
Where they differ
Only the attributes on which Azure Machine Learning and Keras actually diverge.
| Attribute | Azure Machine Learning | Keras |
|---|---|---|
| Pricing model | usage-based | open-source |
| Platforms | Azure Cloud | Python, Google Colab, Jupyter |
| Founded | 1975 | 2015 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Azure Machine Learning
- Automated ML
- Designer (drag-and-drop)
- Notebooks
- MLOps
- Model registry
- Azure Blob Storage
- Azure DevOps
- Power BI
Only in Keras
- Sequential and Functional API
- Pre-built neural network layers
- Model training and evaluation
- Transfer learning
- Model serialization
- TensorFlow
- JAX
- PyTorch
What people use each for
The jobs each tool is most often brought in to do.
Azure Machine Learning
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Keras
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Azure Machine Learning
- Requires knowledge of Azure ecosystem and integration with other Azure services
- Compute resources for training and inference generate separate charges
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
Pricing, plan by plan
Azure Machine Learning
Free- Free TierFree
- Limited compute
- Basic features
- Pay-as-you-go$0.05/hour
- Full platform
- All compute options
- Enterprise features
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
Which should you pick?
Choose Azure Machine Learning if
- You need automated ml.
- You want to start without paying.
- You work on Azure Cloud.
- You also want designer (drag-and-drop).
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.
Questions people ask
- Is Azure Machine Learning or Keras better?
- Neither clearly leads. Azure Machine Learning starts at Free and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Azure Machine Learning or Keras?
- Azure Machine Learning starts at Free and Keras at Free.
- Does Azure Machine Learning or Keras run on more platforms?
- Azure Machine Learning runs on Azure Cloud. Keras runs on Python, Google Colab, Jupyter.
- Can I use Azure Machine Learning for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Azure Machine Learning best used for?
- Azure Machine Learning is most often used for machine learning, data analysis, model training, predictive analytics.
- What can Azure Machine Learning do that Keras cannot?
- Azure Machine Learning covers Automated ML, Designer (drag-and-drop), Notebooks, MLOps. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.
Answered from the vendors’ own pages
Azure Machine Learning: Does Azure Machine Learning have any platform licensing fees?
No, Azure Machine Learning carries no extra cost. You only pay for the underlying compute resources utilized during model training or inference.
SourceKeras: 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.
SourceAzure Machine Learning: What AutoML capabilities does Azure Machine Learning provide?
Azure Machine Learning supports automated model creation for classification, regression, vision, and natural language processing tasks.
SourceKeras: 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.
SourceAzure Machine Learning: Does Azure ML support language model fine-tuning?
Yes, Azure Machine Learning supports fine-tuning of foundation models from providers including OpenAI, Meta, Hugging Face, and Cohere.
SourceKeras: 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.
SourceAzure Machine Learning: What MLOps features are included?
Azure ML includes end-to-end pipeline automation with CI/CD capabilities, managed endpoints for model deployment, and monitoring tools.
SourceKeras: 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.
SourceAzure Machine Learning: Can I access foundation models from multiple vendors?
Yes, Azure Machine Learning provides access to a model catalog with foundation models from Microsoft, OpenAI, Hugging Face, Meta, and Cohere.
SourceKeras: 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.
SourceRelated pages
More on Azure Machine Learning
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