Fundamentals of Deep Learning
PyTorch Model Training Demo Code
In PyTorch, model training typically involves several key steps: defining the model, defining the loss function, selecting an optimizer, preparing a data loader, and writing the training loop. Below is a simple PyTorch model training demo code that implements a basic neural network for handwritten digit recognit ...
Posted on Mon, 06 Jul 2026 16:54:45 +0000 by nokicky
Implementing Decision Tree Classification on MNIST Dataset with Python
Principle Overview
A decsiion tree classifier is a supervised learning algorithm that constructs a tree-like model of decisions based on feature values. The algorithm works by recursively partitioning the dataset into subsets based on the most significant feature that best separates different class labels. Each internal node represents a test o ...
Posted on Thu, 07 May 2026 03:54:56 +0000 by pneudralics