neural network

Introduction set is probably the most beautiful mathematical objects ever discovered, a fractal so intricate that regardless of how much you zoom in, you retain finding infinite detail. But what if we asked a...

In my previous article I explained how YOLOv1 works and tips on how to construct the architecture from scratch with PyTorch. In today’s article, I'm going to deal with the loss function used to...

Neural Network Regressor, we now move to the classifier version. From a mathematical viewpoint, the 2 models are very similar. In truth, they differ mainly by the interpretation of the output and the selection...

are sometimes presented as black boxes. Layers, activations, gradients, backpropagation… it may feel overwhelming, especially when every thing is hidden behind model.fit(). We are going to construct a neural network regressor from scratch using Excel....

computers and Artificial Intelligence, we had established institutions designed to reason systematically about human behavior — the court. The legal system is one in all humanity’s oldest reasoning engines, where facts and evidence...

Within the previous article of this series, operation in all fields of computer science: matrix multiplication. It's heavily utilized in neural networks to compute the activation of linear layers. Nevertheless, activations on their...

how neural networks learned. Train them, watch the loss go down, save checkpoints every epoch. Standard workflow. Then I measured training dynamics at 5-step intervals as an alternative of epoch-level, and all the...

Welcome back to the Tiny Giant series — a series where I share what I learned about MobileNet architectures. Up to now two articles I covered MobileNetV1 and MobileNetV2. Take a look at references ...