myst

The first of a short series by Welch Labs on building a complete neural network in Python. It introduces the data and the architecture of a simple network before later parts cover forward propagation, gradient descent, and backpropagation.

Andreas Spiess explains the basic principles of LoRa and LoRaWAN, their pros and cons, link budget and bandwidth. He shows his own gateway and client sending a message to The Things Network.

Andrej Karpathy builds a bigram character-level language model from scratch, introducing torch.Tensor and the framework of training, sampling and loss evaluation. It is the first step toward a GPT-style Transformer in his makemore series.