To make the most of machine learning you have to train your models right. Here's how to get reliable results from your data.

Machine learning’s impact on technology is significant, but it’s crucial to acknowledge the common issues of insufficient training and testing data.

Optum SVP Sanji Fernando explains how his organization approaches machine learning model training, evaluation, and retraining in this clip from his presentation at Data Summit Connect 2021.

How much time is your machine learning team spending on labeling data — and how much of that data is actually improving model performance? Creating effective training data is a challenge that ...

In membership inference attacks, the adversary can work back from the machine learning algorithm to discover the training data used.

For example, by starting with an ImageNet classifier, researchers in Bangalore, India, used transfer learning to train a model to locate kidneys in ultrasound images using only 45 training examples.

Drenik: How important is quality data in machine learning initiatives, especially in healthcare? Konam: Quality data is essential to train deployable machine learning models in healthcare.