deep-learning-training-and-inference.html

My last "AI 101" post covered the difference between artificial intelligence, machine learning, and deep learning. In this post, I'll cover deep learning training and inference -- two key processes associated with developing and using AI. In the last post, I explained that deep learning (DL) is a special type of machine learning that involves a deep neural network (DNN) composed of many layers of interconnected artificial neurons. Training is the process of "teaching" a DNN to perform a desired AI task (such as image classification or converting speech into text) by feeding it data, resulting in a trained deep learning model. During the training process, known data is fed to the DNN, and the DNN makes a prediction about what the data represents.