Eu flag
pytorch neurosys

PyTorch development services

Accelerate deep learning projects by building neural networks using PyTorch
PyTorch is widely used to create and analyze deep learning (DL) models, e.g. in the field of natural language processing or computer vision, enabling calculations on both CPUs and GPUs. PyTorch is an open-source machine learning (ML) library for Python, that accelerates the path from research prototyping to production deployment, making it a relevant solution for business applications.

What is PyTorch?

Open source project

The ML library developed by the Facebook AI Research lab (FAIR) is an open-source solution used in a growing range of applications. The PyTorch ecosystem is accomplished by serial libraries like Torchvision (for computer vision), Torchtext (for natural language processing), or even Torchaudio (for sound processing).

The packages provide ready-made models and popular datasets, complementing the whole ecosystem. Much of PyTorch's strength results from the open-source character, as it's a sum of countless contributions of machine learning developers and researchers worldwide. Growing as the community behind it grows, PyTorch is nearly unrestricted in building DL/ML solutions.

From research to production

The TorchScript ties up the unified research to production framework. Transforming PyTorch modules into a production-friendly form with TorchScript enables faster execution of models, becoming independent of Python runtime and increasing performance.
pytorch logo black

Why you should consider PyTorch

Pythonic style
It is designed to work smoothly with the Python ecosystem and can be used with popular Python packages.
Mixed-precision training
PyTorch supports methodology for mixed-precision training, combining single-precision and half-precision formats.
Libtorch library core
It is written mostly in C++ to achieve higher performance.
CUDA support
GPUs enable 50x or greater speed-ups in comparison to CPU calculations.
Distributed Data Parallelism
The feature enables running models across multiple machines to scale projects.
Fast & easy execution
PyTorch strives to make writing and using models as easy and productive as possible.
High speed of development
It provides a strong and constantly growing ecosystem.
Widespread adoption
Adoption of PyTorch by e.g. Microsoft and OpenAI assures its further development.
Cloud partners
There’s a possibility to set PyTorch on a vast amount of cloud-based environments from renowned providers.

1h free consultation

Have something specific in mind? Don’t hesitate to contact us for an initial conversation!
Learn more

Building long-lasting partnerships

Comcast logo Toyota logo Safe4 logo CarNext logo Arteel logo tablebooker logo agrovision logo strobbo logo
Pytorch library 1

Features of PyTorch

Dynamic computational graphs
The network’s behavior can be modified at runtime in a dynamic manner, improving efficient model optimization. This allows for great flexibility and facilitates the implementation of a lot of new architectures.
Modular design
Representing the neural networks, modules are fundamental to PyTorch. Modules are individual operations, representing the building blocks of a neural network, in the DL domain called layers. Modules are easy to transform, allowing fast construction of any model.
PyTorch uses special data structures called Tensors to store and operate on multidimensional number arrays. They are similar to NumPy arrays but can be operated on GPUs which significantly speeds up the calculations.
Automatic differentiation for training and evaluating neural networks
Automatic differentiation evaluates functions' derivatives in neural networks. PyTorch contains the Autograd package, providing this functionality to automate processes and create computational graphs with nodes corresponding to mathematical operations.

Benefits of PyTorch

With PyTorch, you can build productive models to process various kinds of data for your benefits
debug icon
Easy debugging
PyTorch’s relationship with Python results in the possibility to use debugging tools of the latter. PyTorch offers the option of viewing any variable in the debugger or simply printing its state.
computer icon
Convenient access to data
The possibility to load practically any type of data – the user can easily use pre-loaded datasets as well as own data using custom DataLoaders.
predictive models icon
Pre-trained models
Instead of breaking the open door each time commonly used models are needed, researchers can freely adapt existing pre-trained neural networks.
recruitment icon
Effortless adoption
A reasonable learning curve and intuitive API make PyTorch a solution easy to adopt among your Python developers team. Fast to introduce in place of similar solutions – an all built-in “plug and play” with minimum configuration.
speed icon
Reduced development time
Thanks to the close relations with Python and a similar syntax, PyTorch supports productivity. Equipped with a simple interface and API, the environment runs smoothly on Windows and Linux. Less hassle, more work done.
customer feedback icon
PyTorch's community
The community of PyTorch users is known as a friendly and helpful environment for developers and researchers. The forum behind it is full of tips on using various architectures, making it the right place for your team to search for answers and support.
Pytorch open source

Where to use PyTorch

Computer vision
Neural networks can be used in object detection, tracking, and image segmentation. The Torchvision package, a part of the PyTorch ecosystem, provides necessary functionalities. The library consists of pre-trained models, popular datasets, and common image transformations for computer vision.
Autonomous vehicles
Tesla and Uber adopt PyTorch in building neural networks, changing the automotive industry. The revolution is possible thanks to multitasking models that collect loads of traffic data. Engineers integrate neural networks to run efficiently in cars, providing real-time reactions in all scenarios.
Robotic solutions in industrial applications
Solutions built using PyTorch support various industries. For one, smart machines let farmers get rid of weeds, reduce costs and pesticide usage. In such cases, PyTorch is the base of a computer vision and machine learning system, recognizing crops from weeds and targeting the latter for spraying.
Artificial data generation
Generative Adversarial Network (GAN) models are trained with two opposing neural networks, one generating new data samples, and the other recognizing real examples. These models are capable of generating images, performing text-to-image translations, or even reconstructing videos from photos.
Natural language processing (NLP)
Training machines to identify and understand human languages enables e.g. gathering information from documents. In automatic text classification and translation, the Torchtext package is used, thanks to pre-built, generic loaders for popular datasets and text resources, including vocabulary objects.
Pytorch laptop

They use PyTorch

Global companies building large, scalable products benefit from using PyTorch. These are among others:
At neurosys 1

At NeuroSYS, we specialize in research and development, harnessing science to benefit business

Our team develops state-of-the-art projects, incorporating the newest technologies like PyTorch, to fully address our clients’ needs. We use PyTorch to create neural networks models, train, validate and test them in the process of building solutions such as computer vision and natural language processing.

PyTorch applications

Would you like to learn more about PyTorch applications? For more in-depth knowledge, see the fields we use PyTorch in:
Computer vision services
Algorithms for recognizing people, places and objects to collect information, analyze it, and build innovative products.
Read more
Natural language processing
Natural language processing algorithms enabling understanding and analysis of human language.
Read more
AWS AI and Azure AI services, lowering the technical threshold and decreasing the go-to-market time for AI-based products.
Read more

Are you ready for your next project?

Unlock your company's full potential with our comprehensive AI and software services. Contact our experts today to discuss how we can drive your success together.

Don’t know how to start?

Check out how you can start working with us with minimum risk and no commitment, getting the maximum value for your business.
1h free consultation
A short, free consultation will help you gain new knowledge about your digital product and get to know us better, no strings attached.
Read more
Technical audit
It is an exhaustive assessment of your application, paying special attention to code quality, key functionalities, proper documentation, and security issues.
Read more
Development process audit
A development process audit will assess a variety of your processes, such as communication and project management – just in 2 weeks.
Read more
Development trial
A development trial helps you to lower the risk of hiring an unsuitable IT company.
Read more

See another cool project that we’ve made

Stay tuned and check what’s new in NeuroSYS

Stay in touch with us:

Don’t miss a thing

Sign up for our newsletter to receive a monthly dose of learning development news, tips, and inspiration.