machine learning Residual Network (ResNet) ResNet makes it possible to train up to hundreds or even thousands of layers and still achieves compelling performance. Thanks to this technique they were able to train a network with 152 layers while still having lower complexity than VGGNet. It achieves a top-5 error rate of 3.57%
machine learning Floating point operations per second (FLOPS) of Machine Learning models In this article, we take a look at the FLOPs values of various machine learning models like VGG19, VGG16, GoogleNet, ResNet18, ResNet34, ResNet50, ResNet152 and others. The FLOPS range from 19.6 billion to 0.72 billion.
machine learning Run a ResNet50 model in ONNX format on TVM Stack with LLVM backend In this guide, we will run a ResNet50 model in ONNX format on the TVM Stack with LLVM backend. You do not need any specialized equipment like GPU and TPU to follow this guide. A simple CPU is enough.
