PyTorch Reviews

Name: PyTorch
Brand: PyTorch
Rating: 4.3 (12 reviews)

4.3 out of 5

12 reviews
100% willing to recommend

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.

Get the PyTorch Buyer's Guide and find out what your peers are saying about PyTorch, Microsoft Azure Machine Learning Studio, Google Vertex AI and more!

PyTorch is the #8 ranked solution in top AI Development Platforms. PeerSpot users give PyTorch an average rating of 8.6 out of 10. Based on the analysis of the 12 most recent PyTorch reviews, the overall sentiment is positive, with a sentiment score of 7.2. PyTorch is most commonly compared to Microsoft Azure Machine Learning Studio: PyTorch vs Microsoft Azure Machine Learning Studio. PyTorch is popular among the large enterprise segment, accounting for 64% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a manufacturing company, accounting for 30% of all views.

Helped 824,053 peers since 2012

Featured reviews

Karthikeyan Katkam

AWS Engineer at Neurolov.ai

I like PyTorch's scalability. I can use a very large scale of models that I can easily train in. OpenCV is also there, however, compared to OpenCV, PyTorch is better for converting actual text data to visual data. I'm actually developing my own tool for the application that I'm building for myself. It's a crypto exchange.

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Praveen Kumar Tiwari

Team Lead at Tech Mahindra Limited

PySearch is the best option for developing any project in the AIML domain. It's a top framework for running and managing projects efficiently in the current market scenario. It allows you to attach databases and manage all aspects of your project. It’s reliable, secure and user-friendly. It allows you to develop any AIML project efficiently. If any bugs or issues arise, you can manage them effectively. There are many services available for handling various tasks.

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Jithin James

Financial Analyst 4 (Supply Chain & Financial Analytics) at Juniper Networks

The most valuable feature would be the solution’s performance. The product is more advanced than the other libraries that I have used. Since every functionality is production-ready, I can easily write code. I don't have to rewrite the code for production. It has production-ready code from the start. The tool is very user-friendly. It took us a week to learn how to use it. It's straightforward to learn.

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PyTorch mindshare

As of December 2024, the mindshare of PyTorch in the AI Development Platforms category stands at 1.5%, down from 2.2% compared to the previous year, according to calculations based on PeerSpot user engagement data.

AI Development Platforms

PeerAnalyst reports

Type	Title	Date
Category	AI Development Platforms	Dec 22, 2024	Download
Product	Reviews, tips, and advice from real users	Dec 22, 2024	Download
Comparison	PyTorch vs Azure OpenAI	Dec 22, 2024	Download
Comparison	PyTorch vs Google Vertex AI	Dec 22, 2024	Download
Comparison	PyTorch vs Microsoft Azure Machine Learning Studio	Dec 22, 2024	Download

Title	Rating	Mindshare	Recommending
Microsoft Azure Machine Learning Studio	3.8	12.1%	93%	58 interviews Add to research
Google Vertex AI	4.2	23.7%	100%	10 interviews Add to research

Valuable Features

"PyTorch allows me to build my projects from scratch."
"I like PyTorch's scalability."
"We use PyTorch libraries, which are working well. It's very easy."

Room for Improvement

"I do not have any complaints."
"The analyzing and latency of compiling could be improved to provide enhanced results."
"We faced an issue with PyTorch due to version incompatibility. PyTorch has no latest version after v12.3."

ROI

Pricing

PyTorch is an open-source tool, available for free, and widely regarded as affordable for enterprises. Users appreciate the absence of licensing fees unless highly specialized functions are required, in which case consulting experts or opting for paid support might be necessary. The accessibility of resources online ensures flexibility, and while no paid plans are needed initially, options for additional support exist if required.

"The solution is affordable."
"PyTorch is open source."
"PyTorch is open-sourced."

Popular Use Cases

Service and Support

Deployment

Scalability

Stability

Users find PyTorch stable, with most not experiencing stability problems. Some mention environmental issues when handling heavy workloads. Transitions between versions can cause issues, though solutions exist to handle these breakdowns. Upgrading versions may introduce errors, but stability is generally rated highly. Despite needing to enhance their hardware to support multiple models, these challenges are not specific to PyTorch. Stability receives positive feedback from various users.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our PyTorch Buyer's Guide for additional reliable information.

Review data by company size

By reviewers

By visitors reading reviews

Top industries

By visitors reading reviews

Manufacturing Company

30%

Computer Software Company

11%

Healthcare Company

Financial Services Firm

Comms Service Provider

Educational Organization

University

Energy/Utilities Company

Government

Retailer

Real Estate/Law Firm

Wholesaler/Distributor

Insurance Company

Legal Firm

Non Profit

Recreational Facilities/Services Company

Transportation Company

Construction Company

Sports Company

Hospitality Company

Logistics Company

Wellness & Fitness Company

Media Company

Compare PyTorch with alternative products

Learn more about PyTorch

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.