Google Cloud AI vs. Keras

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud AI
Score 8.3 out of 10
N/A
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.N/A
Keras
Score 7.8 out of 10
N/A
Keras is a Python deep learning libraryN/A
Pricing
Google Cloud AIKeras
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Google Cloud AIKeras
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
Best Alternatives
Google Cloud AIKeras
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Posit
Posit
Score 9.1 out of 10
Posit
Posit
Score 9.1 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud AIKeras
Likelihood to Recommend
10.0
(6 ratings)
8.1
(6 ratings)
Likelihood to Renew
10.0
(1 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
7.7
(2 ratings)
Support Rating
7.3
(3 ratings)
8.2
(2 ratings)
Implementation Rating
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Google Cloud AIKeras
Likelihood to Recommend
Google
Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
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Open Source
Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level TensorFlow API or Pytorch
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Pros
Google
  • good conversion from the voice to the text
  • speed in the conversion from voice to text
  • time-saving in the conversion activity
  • analysis of the results of the conversion in real time
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Open Source
  • One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations.
  • It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast.
  • It also provides functionality to develop models on mobile device.
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Cons
Google
  • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
  • Customization of existing modules and libraries is harder and it does need time and experience to learn.
  • Google Cloud AI can do a better job in providing better support for Python and other coding languages.
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Open Source
  • As it is a kind of wrapper library it won't allow you to modify everything of its backend
  • Unlike other deep learning libraries, it lacks a pre-defined trained model to use
  • Errors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logs
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Likelihood to Renew
Google
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
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Open Source
No answers on this topic
Usability
Google
So far we have not had any problems with the application, it is extremely easy to use and it is also easy to install. It does not require much training since the instruction is quite clear for its execution and application in the procedures of the company. The team in charge of this application is very pleased to work with this app.
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Open Source
I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.
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Support Rating
Google
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
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Open Source
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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Implementation Rating
Google
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
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Open Source
No answers on this topic
Alternatives Considered
Google
These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
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Open Source
Keras is good to develop deep learning models. As compared to TensorFlow, it's easy to write code in Keras. You have more power with TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to MATLAB, I will always prefer Keras as it is easy and powerful as well.
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Return on Investment
Google
  • Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
  • We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
  • The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
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Open Source
  • Easy and faster way to develop neural network.
  • It would be much better if it is available in Java.
  • It doesn't allow you to modify the internal things.
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