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Education & E-Learning · head to head

360Learning vs Keras

360Learning logo

360Learning

Education & E-Learning

Collaborative learning that transforms L&D

From
On request
Rated
-
Keras logo

Keras

Machine Learning & Data Science

Deep learning API for humans

From
Free
Rated
-

The short version

  • Only Keras has a free tier, so it costs nothing to try first.
  • Each has a real cost: 360Learning the published Team plan at $8 per user per month covers up to 100 users; beyond that pricing is custom; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: 360Learning covers Collaborative authoring, Keras covers Sequential and Functional API.

Where they differ

Only the attributes on which 360Learning and Keras actually diverge.

Attributes where 360Learning and Keras differ
Attribute360LearningKeras
Starting priceOn requestFree
Pricing modelsubscriptionopen-source
Free tierNoYes
PlatformsWeb, IOS, Android, APIPython, Google Colab, Jupyter
CategoryEducation & E-LearningMachine Learning & Data Science
Founded20102015

Identical on both: user rating (Not yet rated).

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 360Learning

  • Collaborative authoring
  • AI-powered recommendations
  • Social learning
  • Assessments
  • Mobile learning
  • Analytics
  • Integrations
  • Gamification

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.

360Learning

  • Collaborative course authoring by internal subject matter expertsnot Keras
  • Onboarding and compliance training deliverynot Keras
  • Upskilling programmes tracked across a workforcenot Keras
  • Customer and partner trainingnot Keras

Keras

  • Machine learningnot 360Learning
  • Data analysisnot 360Learning
  • Model trainingnot 360Learning
  • Predictive analyticsnot 360Learning

Where each one falls short

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

360Learning

  • The published Team plan at $8 per user per month covers up to 100 users; beyond that pricing is custom
  • Business and Enterprise pricing is not published
  • Priority SLA, dedicated technical support and premium onboarding are Enterprise only
  • Business and Enterprise plans are typically annual contracts rather than monthly

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

360Learning

On request
  • Team$undefined/month
    • Collaborative authoring
    • Course library
    • Reporting
  • Business$undefined/month
    • All Team
    • Integrations
    • Advanced analytics
  • Enterprise$undefined/month
    • All Business
    • Custom development
    • Dedicated success

Keras

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

Which should you pick?

Choose 360Learning if

  • You need collaborative authoring.
  • You work on Web, IOS, Android, API.
  • You also want ai-powered recommendations.

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 360Learning or Keras better?
Neither clearly leads. 360Learning starts at On request and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, 360Learning or Keras?
Keras has a free tier; the other does not. Paid plans start at On request for 360Learning and Free for Keras.
Does 360Learning or Keras run on more platforms?
360Learning runs on Web, IOS, Android, API. Keras runs on Python, Google Colab, Jupyter.
Can I use Keras for free?
Yes. Keras has a free tier, so you can try it without paying. 360Learning starts at On request.
What is 360Learning best used for?
360Learning is most often used for collaborative course authoring by internal subject matter experts, onboarding and compliance training delivery, upskilling programmes tracked across a workforce, customer and partner training. Of those, collaborative course authoring by internal subject matter experts and onboarding and compliance training delivery are not what Keras is typically brought in for.
What can 360Learning do that Keras cannot?
360Learning covers Collaborative authoring, AI-powered recommendations, Social learning, Assessments. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

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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