Machine Learning
Machine learning is the science of teaching machines from data and making decisions without being programmed to do exactly that. Deep Learning, a subset of machine learning, uses neural networks to perform an advanced form of predictive analytics. Machine learning can be broadly divided into three categories:
Supervised learning: trains models on labeled data sets, allowing them to accurately recognize patterns, predict results or classify new data.
Unsupervised learning: trains models to sort through unlabeled data sets to discover underlying relationships or clusters.
Reinforcement learning: takes a different approach, in which models learn to make decisions by acting as agents and receiving feedback on their actions.
There is also semi-supervised learning, which combines aspects of supervised and unsupervised learning. This technique uses a small amount of labeled data and a larger amount of unlabeled data, thereby improving learning accuracy while reducing the need for labeled data, which can be time and labor intensive to procure.
