In this tutorial, we demonstrate how we simulate a privacy-preserving fraud detection system using Federated Learning without relying on heavyweight frameworks or complex infrastructure. We build a ...
JAX is one of the fastest-growing tools in machine learning, and this video breaks it down in just 100 seconds. We explain how JAX uses XLA, JIT compilation, and auto-vectorization to turn ordinary ...
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Abstract: With an emphasis on convolutional neural networks (CNNs), this research does a thorough analysis of the effectiveness and suitability of the TensorFlow and PyTorch frameworks for image ...
It would be nice to know exactly on which versions of pytorch and tensorflow these tutorials were tested. Also, do you use tensorflow ? by looking at the code it does seems so..
The model itself is a regular Pytorch nn.Module or a TensorFlow tf.keras.Model (depending on your backend) which you can use as usual. This tutorial explains how to integrate such a model into a ...
Scaling TensorFlow, PyTorch, and MXNet using MVAPICH2 for High-Performance Deep Learning on Frontera
Abstract: Frontera is the largest NSF-funded cluster in the US and comprises of 8,008 nodes equipped with the latest Intel Xeon processors (Cascade-Lake). In this paper, we explore the potential of ...
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