In these series of articles, we will provide you with a brief dictionary of terms surrounding data science including AI, machine learning, and deep learning.
So, what is Long Short Term Memory in Data Science in 2020?
Recurrent neural networks, of which long short-term memory units are the most powerful and well known subset, are a type of artificial neural network designed to recognize patterns in sequences of data, such as numerical times series data emanating from sensors, stock markets and government agencies, but also including text, genomes, handwriting and the spoken word.
A long short-term memory network is a special kind of recurrent neural network which is optimized for learning from and acting upon time-related data which may have undefined or unknown lengths of time between relevant events. Long short-term memory networks work very well on a wide range of problems and are now widely used. They were introduced in 1997 by Hochreiter & Schmidhuber, and were refined and popularized by many subsequent researchers.