Elon Musk made it clear that he doesn’t like Facebook, however, Tesla still uses one piece of technology that comes from Zukenberg’s laboratory. We can bet that it made its way into SpaceX as well and that it was an important part of the recent launch too. This technology has a big advocate in the AI world and that is Yan LeCunn, father of modern Convolutional Neural Networks. That is correct, we are talking about PyTorch. This deep learning framework is extremely popular among the research community and we can witness that in the past couple of years it gained popularity in the industry as well.
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Generally speaking PyTorch as a tool has two big goals. The first one is to be NumPy for GPUs. This doesn’t mean that NumPy is a bad tool, it just means that it doesn’t utilize the power of GPUs. The second goal of PyTorch is to be a deep learning framework that provides speed and flexibility. That is why it is so popular in the research community because it provides a platform in which users can quickly perform experiments. Apart from that, building models in PyTorch is very easy. In the past couple of weeks, we have been writing about this rising technology. In the following three articles, you can learn PyTorch’s basic concepts, find out how to utilize them for building simple neural networks and how to deploy those networks using TorchServe:
- PyTorch for Beginners – Basic Concepts
- PyTorch for Beginners – Building Neural Networks
- PyTorch for Beginners – Deploying Models with TorchServe
Thank you for reading!
Nikola M. Zivkovic
CAIO at Rubik's Code
Nikola M. Zivkovic a CAIO at Rubik’s Code and the author of book “Deep Learning for Programmers“. He is loves knowledge sharing, and he is experienced speaker. You can find him speaking at meetups, conferences and as a guest lecturer at the University of Novi Sad.
Rubik’s Code is a boutique data science and software service company with more than 10 years of experience in Machine Learning, Artificial Intelligence & Software development. Check out the services we provide.
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