In PyTorch, when working with data for deep learning models, it is common to create a custom dataset class that … Más
Autor: Yolanda MURIEL
BIM Architect, Building engineer
Barcelona, Spain
ARTIFICIAL INTELLIGENCE (16) – Deep learning (14) Understanding Backpropagation (2)
Another interesting type of non-linearity is the ReLU function, which sets any negative neuron output to zero. In a fully … Más
ARTIFICIAL INTELLIGENCE (15) – Deep learning (13) Understanding Backpropagation (1)
The issue with backpropagation is that it acts as a “leaky abstraction.” Calling backpropagation a leaky abstraction means that, although … Más
ARTIFICIAL INTELLIGENCE (14) – Deep learning (12) Running and Debugging a Deep Learning Project in Visual Studio Code
This article is a Step‑by‑Step Guide of how Running and Debugging a Deep learning Model/Project in Visual Studio Code. Install … Más
ARTIFICIAL INTELLIGENCE (13) – Deep learning (11) Understanding Decision Thresholds: Why “High” and “Low” Thresholds Matter
In many machine‑learning models—especially logistic regression—we make predictions that look like a score between 0 and 1. This score can … Más
ARTIFICIAL INTELLIGENCE (12) – Deep learning (10) Why Only the First Layer of a CNN Can Be Visualised as an RGB Image
Convolutional Neural Networks (CNNs) are made of many layers stacked together, each transforming the input image into more abstract representations. … Más
Debe estar conectado para enviar un comentario.