Neuton vs. Pytorch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Neuton
Score 9.0 out of 10
N/A
Bell Integrator offers Neuton, an automated machine learning (Automated ML) application supplying AI learning and assistance to analytics and or business processes.N/A
Pytorch
Score 9.3 out of 10
N/A
Pytorch is an open source machine learning (ML) framework boasting a rich ecosystem of tools and libraries that extend PyTorch and support development in computer vision, NLP and or that supports other ML goals.N/A
Pricing
NeutonPytorch
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
NeutonPytorch
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
NeutonPytorch
Top Pros

No answers on this topic

Top Cons

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Best Alternatives
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Medium-sized Companies
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Score 9.1 out of 10
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Score 9.1 out of 10
Enterprises
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All AlternativesView all alternativesView all alternatives
User Ratings
NeutonPytorch
Likelihood to Recommend
9.0
(1 ratings)
9.4
(5 ratings)
User Testimonials
NeutonPytorch
Likelihood to Recommend
Bell Integrator
The machine learning modeling and time-series forecasting are the best things that Neuton's platform provides. Researchers in the field of healthcare, marketing and various other industries can use this platform to get more in-depth insights into the dataset that they have been working on. Neuton.ai is going to bring in image detection and text analysis in the future which makes the perfect choice for people from product management profiles and various Data Science backgrounds.
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Open Source
They have created Pytorch Lightening on top of Pytorch to make the life of Data Scientists easy so that they can use complex models they need with just a few lines of code, so it's becoming popular. As compared to TensorFlow(Keras), where we can create custom neural networks by just adding layers, it's slightly complicated in Pytorch.
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Pros
Bell Integrator
  • Exploratory Data Analysis
  • Machine learning modeling
  • Time Series forecasting
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Open Source
  • Provides Benchmark datasets to test your custom algorithm
  • Provides with a lot of pre-coded neural net components to use for your flow
  • Gives a framework to write really abstract code.
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Cons
Bell Integrator
  • User Onboarding with Google cloud platform is the most confusing part, this can be definitely be improved
  • UI of the platform
  • Front end of the website seems simple, little more features can be added so that people or users can navigate to various pages and know more about the platform
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Open Source
  • Distributed data parallel still seems to be complicated
  • Support for easy deployment to servers
  • Torchvision to have support for latest models with pertained weights
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Alternatives Considered
Bell Integrator
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Open Source
As I described in previous statements, Pytorch is much better suited than TensorFlow from a software development look. This Pythonic idea was then taken and repeated by all the other frameworks. You can get to better performance models by better understanding the deep learning model code, so I think the choice of Pytorch is easy and simple.
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Return on Investment
Bell Integrator
  • We have had 2% increase in our market reach using the EDA from the Neuton's Platform
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Open Source
  • I'd estimate I can build a model 50% faster on pytorch vs other frameworks
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