Associate Data Analyst at a financial services firm with 10,001+ employees
Apr 16, 2021
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.
Freelance AI Engineer at a tech services company with self employed
Nov 17, 2020
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.
It’s reliable, secure and user-friendly. It allows you to develop any AIML project efficiently.
PySearch is the best option for developing any project in the AIML domain.
The product is easy to install.
Data Scientist. at a computer software company with 501-1,000 employees
Mar 27, 2024
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.
Associate Data Analyst at a financial services firm with 10,001+ employees
Apr 16, 2021
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.
