Deep Learning frameworks are one of the crucial components for building and training AI systems to understand the data context, process complex tasks & deliver highly precise results. These deep learning software libraries are the cornerstone of most advanced use cases of data science like facial recognition, NLP applications, medical imaging, generative chatbots and much more.
TensorFlowl and PyTorch, the two most familiar deep learning frameworks in the AI Space, have their own characteristics – serving as ideal choices for distinctive goals in the AI adoption journey like scalability, performance optimization, high-level integration, etc.
Download our infographic to understand the specialities & differences between the two and pick the right choice of deep learning framework for your revolutionary AI application.
