Advanced and useful framework for Data Science.
August 31, 2022
Advanced and useful framework for Data Science.
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Pytorch
We use Pytorch for Data Science related projects; it is a very advanced framework for doing Machine/Deep Learning for people who are already familiar with python. It has a lot of datasets and models integrated that can be used just with a few lines of code to create a quick POC. It's very easy to write our neural networks with Pytorch.
- It's easy to write custom neural networks.
- It optimises algebraic operation.
- It has good support for computation on GPUs.
- It should have support for Java also as Java is one of the most popular language.
- They should make things more easy if we want to use GPUs for computation.
- They should keep adding the latest models so that we can easily load them for use for further fine-tuning.
- Most popular datasets like mnist, etc are integrated.
- Fine-tuning models is easy.
- Community support is good.
- It helped us creating quick POCs for customers.
- We can do customisation as we need.
- There is a learning curve so people need to spend some time for getting used to it.
- TensorFlow and Keras
Saving and loading Machine/Deep Learning models is very easy with Pytorch. It provides visualization capabilities when combined with Tensorboard, and mathematical operations are highly optimized. Easy to understand for a person who is an expert in Python. It takes significantly less time to create valuable POCs as most of the things are inbuilt.
Do you think Pytorch delivers good value for the price?
Yes
Are you happy with Pytorch's feature set?
Yes
Did Pytorch live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Pytorch go as expected?
I wasn't involved with the implementation phase
Would you buy Pytorch again?
Yes