Dataloop vs. Keras

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataloop
Score 0.0 out of 10
N/A
Dataloop's platform is presented as a one-stop shop for generating datasets from raw visual data - It includes data management environment, intuitive annotation tool with automatic annotation capabilities, and data QA and debug tools.N/A
Keras
Score 7.0 out of 10
N/A
Keras is a Python deep learning libraryN/A
Pricing
DataloopKeras
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DataloopKeras
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
DataloopKeras
User Ratings
DataloopKeras
Likelihood to Recommend
-
(0 ratings)
8.1
(0 ratings)
Usability
-
(0 ratings)
7.7
(0 ratings)
Support Rating
-
(0 ratings)
8.2
(0 ratings)
User Testimonials
DataloopKeras
Likelihood to Recommend
No answers on this topic
I would recommend it for use when anyone wants to quickly develop a neural network. Or if a user is solving any machine learning problem that includes deep learning. And this kind of problem will be like image recognition, face recognition, doing some text analysis using deep learning which includes LSTM or some other algorithm.
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Pros
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  • Implementing neural networks and deep learning models is easy with this.
  • Data processing is easy with Python and Keras. Keras helps a lot and has a good collection of functions to do data processing.
  • It has good integration with other devices like Android.
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Cons
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  • I didn't face any issue so far.
  • The only thing, you can't modify everything in this. So it's not recommended for constructing highly optimised algorithms.
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Usability
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The reason for giving this much rating. 1. It makes my job really easy and fast. 2. Strong community support. 3. Overall cost.
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Support Rating
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Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.
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Alternatives Considered
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As Keras is the high level API, so using Keras, we don't have to be bothered by the low level TensorFlow complexity, and we can reduce a lot coding and testing efforts.
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Return on Investment
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  • It helped me in learning the basic concept of deep learning by having hands-on experience.
  • It has helped us to implement our NN with very little time.
  • It doesn't give you the whole power to customize your neural network. If you want that then you have to shift to TensorFLow
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ScreenShots