ChatGPT API

People the world over are using ChatGPT to transform the way they do business. Sales executives use it to create scoping documents from transcripts of conversations with clients. Marketing directors […]

Understanding ChatGPT

Unless you’ve lived in a cave for the last few months, you’ve heard of ChatGPT. It’s a deep-learning model (neural network) created by OpenAI whose ability to generate human-like prose […]

Object Detection

My previous post introduced two popular algorithms for detecting faces in photographs: Viola-Jones, which relies on machine learning, and MTCNNs, which rely on deep learning.

Face Detection

My previous post demonstrated how to use transfer learning with a CNN trained on millions of facial images to build a facial-recognition model that is remarkably adept at identifying faces.

Data Augmentation

My previous post demonstrated how to use transfer learning to build a model that with just 300 training images can classify photos of three different types of Arctic wildlife with 95% accuracy.

Transfer Learning

My post introducing convolutional neural networks (CNNs) used a dataset with photos of Arctic foxes, polar bears, and walruses to train a CNN to recognize Artic wildlife.

Pretrained CNNs

Given a set of images with a relatively high degree of separation between classes, it is perfectly feasible to train a CNN to classify those images on a typical laptop or PC.