PyTorch
PyTorch is an open-source deep learning framework, originally from Meta, used to build and train neural networks.
At a glance
- Field
- AI & Machine Learning
- Best for
- Deep learning models
- Related service
- AI & Machine Learning
- First conversation
- Free, no obligation
Why businesses use PyTorch
When a business problem needs a custom AI model, for example recognising defects in images or forecasting demand, PyTorch is one of the main tools used to build and train it.
How PyTorch works
Developers define a neural network, feed it labelled examples, and let it gradually adjust itself to make better predictions. Trained models are then deployed behind an API for your applications to use.
What it's used for
- 01Custom image and video models
- 02Fine-tuning language models
- 03Forecasting and prediction
- 04Research and prototyping
Benefits
- Industry and research standard
- Flexible and intuitive
- Large ecosystem of pretrained models
- Runs on CPUs and GPUs
Good to know
Every technology has trade-offs. We will always tell you when another option fits better.
- Training custom models needs quality labelled data
- GPU infrastructure can be costly
How MOKRIN uses PyTorch
We use PyTorch as part of our ai & machine learning work, mainly for deep learning models. It is one of the tools we recommend when it fits your goals, budget, and existing systems, and you own everything we build with it.
- AI assistants and chatbots
- Document processing
- Predictions and recommendations
- Computer vision
AI & Machine Learning
Related technologies
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