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PyTorch OverviewUNIXBusinessApplication

PyTorch is #4 ranked solution in top AI Development Platforms. PeerSpot users give PyTorch an average rating of 9.0 out of 10. PyTorch is most commonly compared to OpenVINO: PyTorch vs OpenVINO. PyTorch is popular among the large enterprise segment, accounting for 74% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a comms service provider, accounting for 20% of all views.
Buyer's Guide

Download the AI Development Platforms Buyer's Guide including reviews and more. Updated: July 2022

What is PyTorch?

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.

PyTorch Pricing Advice

What users are saying about PyTorch pricing:
  • "PyTorch is an open-source solution."
  • "It is free."
  • PyTorch Reviews

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    Associate Data Analyst at a financial services firm with 10,001+ employees
    Real User
    Top 10
    A highly user-friendly open-source machine learning library
    Pros and Cons
    • "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."
    • "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."

    What is our primary use case?

    I work within the field of NLP and data logistics, but most of the information is stored in the description. I mostly use NLP algorithms to extract the sentiment or the similarity if they have a similarity score calculation. For example, something like the windshield cracking, or something extremely severe like a garage burning, or multiple car damage. 

    The NLP tasks don't deal with the financial data directly but use extra information to get some insights. It's not really a good practice in India to use deep learning models directly on financial data because of audit reasons.

    What is most valuable?

    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 one of the easiest tools and takes the hint on its own. I was quite happy about its existence.

    What needs improvement?

    None come to mind.

    For how long have I used the solution?

    I have been using PyTorch for about three months.

    Buyer's Guide
    AI Development Platforms
    July 2022
    Find out what your peers are saying about PyTorch, OpenVINO, Microsoft and others in AI Development Platforms. Updated: July 2022.
    619,967 professionals have used our research since 2012.

    What do I think about the stability of the solution?

    I think PyTorch is a stable solution. I had to upgrade the box it was running on several times to handle the load from many models I was running parallely, but that's not specific to PyTorch. But I think that was more of an environmental issue and not a problem with PyTorch. There was a transition period where the initial models weren't production-ready, and I had slated Caffe2. But I think the current version is pretty good and pretty stable.

    Which solution did I use previously and why did I switch?

    Initially, I was using the Keras addon, and these are like high-level wrappers for TensorFlow. I started to look at PyTorch, and it was quite easy to learn and easy to implement.

    PyTorch is a new insert, and I'm the only one using it. Most of my teammates are on TensorFlow because that's something that has been stable for a long time. I'm just showing them that it's easy to use PyTorch. 

    I was also experimenting with MXNet, which is part of Amazon Deep Learning for three months. I've been providing proof of concepts for existing models using these different frameworks that are available in the marketplace.

    How was the initial setup?

    The initial setup is quite easy as it is just a library install. The model building itself is fairly simple because it's pythonic. It was more natural and followed how Python should be used. I would say that it helps the structure.

    What about the implementation team?

    We just followed all these open source guys out there. They had like a lab for data science and a data lab in our company, which is basically an incident technology solutions provider. Just like bringing an analytics practice into the mix. But it's still a work in progress, and we just use a Python server that has all the latest policies installed. You just query whatever you want. The Ops and the support team take care of it.

    What's my experience with pricing, setup cost, and licensing?

    PyTorch is an open-source solution.

    What other advice do I have?

    I would recommend this solution because PyTorch is like a godsend.

    On a scale from one to ten, I would give PyTorch a ten.

    Which deployment model are you using for this solution?

    On-premises

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Google
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    PeerSpot user
    Freelance AI Engineer at a tech services company with self employed
    Real User
    Top 10
    Good interface, free of cost, and quite stable
    Pros and Cons
    • "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."
    • "There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."

    What is our primary use case?

    It is mostly used for everything that is connected to machine learning, data science, training, and other similar things.

    What is most 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. 

    What needs improvement?

    There is not enough documentation about some methods and parameters. It is sometimes difficult to find information.

    For how long have I used the solution?

    I have been using PyTorch for almost two years.

    What do I think about the stability of the solution?

    It is quite stable. Currently, I am the only user.

    What do I think about the scalability of the solution?

    It is scalable.

    How are customer service and technical support?

    They don't have support. It is an open-source kind of thing. It is not really open source, but openly available.

    How was the initial setup?

    It is more or less straightforward. I sometimes have problems installing it. The deployment duration depends on the size of the model. It could take one hour. Sometimes, the whole process can take more than several weeks.

    What about the implementation team?

    It was an in-house installation.

    What's my experience with pricing, setup cost, and licensing?

    It is free.

    Which other solutions did I evaluate?

    I also considered TensorFlow. I don't remember why exactly I chose PyTorch instead of TensorFlow, but I think I didn't evaluate much. It was just like one of the two options, so I went for PyTorch.

    What other advice do I have?

    I would definitely recommend this solution. I would rate PyTorch an eight out of ten.

    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    PeerSpot user