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."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."
"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."
"The initial setup is very straightforward."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"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."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"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."
"The tool is very user-friendly."
"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."
"It's been pretty scalable in terms of using multiple GPUs."
"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."
"The framework of the solution is valuable."
"Customizations are very difficult, and they take time."
"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."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"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."
"The initial setup was straightforward for me but could be difficult for others."
"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."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"PyTorch could make certain things more obvious. Even though it does make things like defining loss functions and calculating gradients in backward propagation clear, these concepts may confuse beginners. We find that it's kind of problematic. Despite having methods called on loss functions during backward passes, the oral documentation for beginners is quite complex."
"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."
"On the production side of things, having more frameworks would be helpful."
"I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques."
"The training of the models could be faster."
Google Cloud AI Platform is ranked 6th in AI Development Platforms with 7 reviews while PyTorch is ranked 11th in AI Development Platforms with 6 reviews. Google Cloud AI Platform is rated 7.8, while PyTorch is rated 8.6. 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.
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