Google Cloud AI Platform vs PyTorch comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Google Cloud AI Platform and PyTorch based on real PeerSpot user reviews.

Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Google Cloud AI Platform vs. PyTorch Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture.""The initial setup is very straightforward.""On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients.""I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms.""A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick.""Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour.""The solution is able to read 90% of the documents correctly with a 10% error rate."

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"The framework of the solution is valuable.""Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful.""I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code.""yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."

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Cons
"I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite.""The initial setup was straightforward for me but could be difficult for others.""The solution can be improved by simplifying the process to make your own models.""One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform.""It could be more clear, and sometimes there are errors that I don't quite understand.""At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning.""Customizations are very difficult, and they take time."

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"The training of the models could be faster.""There is not enough documentation about some methods and parameters. It is sometimes difficult to find information.""On the production side of things, having more frameworks would be helpful.""I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."

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Pricing and Cost Advice
  • "The price of the solution is competitive."
  • "For every thousand uses, it is about four and a half euros."
  • "The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."
  • "The licenses are cheap."
  • "The pricing is on the expensive side."
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  • "It is free."
  • "PyTorch is an open-source solution."
  • "It is free."
  • More PyTorch Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up… more »
    Top Answer:It's a host of use cases depending on, again, the the client requirement.
    Top Answer:yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily.
    Top Answer:It is free. There are no additional fees unless you want something very specialized. In that case, you might need to consult with an expert.
    Top Answer:On the production side of things, having more production tooling frameworks would be helpful. TensorFlow has a lot of elaborate frameworks e.g. for serving models, and that's one area where PyTorch… more »
    Ranking
    6th
    Views
    3,376
    Comparisons
    2,502
    Reviews
    5
    Average Words per Review
    511
    Rating
    7.8
    11th
    Views
    1,460
    Comparisons
    1,070
    Reviews
    2
    Average Words per Review
    383
    Rating
    9.0
    Comparisons
    Learn More
    Google
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    PyTorch
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    Overview

    Google AI Platform is a managed service that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework that powers many Google products, from Google Photos to Google Cloud Speech.

    We've built this course as an introduction to deep learning. Deep learning is a field of machine learning utilizing massive neural networks, massive datasets, and accelerated computing on GPUs. Many of the advancements we've seen in AI recently are due to the power of deep learning. This revolution is impacting a wide range of industries already with applications such as personal voice assistants, medical imaging, automated vehicles, video game AI, and more.

    In this course, we'll be covering the concepts behind deep learning and how to build deep learning models using PyTorch. We've included a lot of hands-on exercises so by the end of the course, you'll be defining and training your own state-of-the-art deep learning models.

    Sample Customers
    Carousell
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company14%
    Financial Services Firm11%
    University10%
    Manufacturing Company9%
    VISITORS READING REVIEWS
    Manufacturing Company20%
    University10%
    Computer Software Company10%
    Educational Organization8%
    Company Size
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise14%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise11%
    Large Enterprise67%
    Buyer's Guide
    Google Cloud AI Platform vs. PyTorch
    March 2024
    Find out what your peers are saying about Google Cloud AI Platform vs. PyTorch and other solutions. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Google Cloud AI Platform is ranked 6th in AI Development Platforms with 7 reviews while PyTorch is ranked 11th in AI Development Platforms with 4 reviews. Google Cloud AI Platform is rated 7.8, while PyTorch is rated 9.0. The top reviewer of Google Cloud AI Platform writes "An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data". On the other hand, the top reviewer of PyTorch writes "Offers good backward compatible and simple to use". Google Cloud AI Platform is most compared with Microsoft Azure Machine Learning Studio, IBM Watson Machine Learning, Google Vertex AI, Azure OpenAI and IBM Watson OpenScale, whereas PyTorch is most compared with OpenVINO, MXNet, Microsoft Azure Machine Learning Studio, Caffe and Google Vertex AI. See our Google Cloud AI Platform vs. PyTorch report.

    See our list of best AI Development Platforms vendors.

    We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.