Neural

in supply-chain planning has traditionally been treated as a time-series problem. Each SKU is modeled independently. A rolling time window (say, last 14 days) is used to predict tomorrow’s sales. Seasonality is captured, promotions are added,...

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...

Even networks long considered “untrainable” can learn effectively with a little bit...

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...

as a black box. We all know that it learns from data, however the query is it truly learns. In this text, we are going to construct a tiny Convolutional Neural Network (CNN)...

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...