What is Data Labeling ? | Prepare Your Data for ML and AI | Attaching meaning to digital data 27

data labeling in the context of machine learning  is the process of detecting and tagging data   samples it is the process of attaching meaning  to digital data the process can be manual but   is usually performed or assisted by software  data labeling is an important part of data   pre-processing for ML particularly for supervised  learning in which both input and output date to   are labeled for classification to provide a  learning basis for future data processing for   example a system training to identify animals in  images might be provided with multiple images of   various types of animals from which it would  learn the common features of each enabling it   to correctly identify the animals in unlabeled  images but how does it work exactly we know   that ml and deep learning systems often require  massive amounts of data to establish a foundation   for reliable learning patterns the data they used  to inform learning must be labeled or annotated   which means that everything or sometimes only  the most important things have to be identified   and localized in the image more it must be  labeled based around data features that help   the model organize the data into patterns  that produce a desired answer a properly   labeled data set provides a ground truth that  the ML model uses to check its predictions for   accuracy and to continue refining its algorithm  errors in data labeling impair the quality of   the training data set and the performance of any  predictive models it's used for to mitigate this   many organizations take a human-in-the-loop H  ITL approach which is called a data label and   maintaining human involvement in training and  testing data models throughout their iterative   growth there are several methods to structure and  label its data maintaining this human involvement   either by using crowdsourcing where a third  party platform gives an enterprise access to   many workers at once or using contractors where  an enter can hire temporary freelance workers to   process and label data it is possible to make  use of an house staff to wear an enterprise   can use its existing employees to process data  a recent report from AI research and advisory   firm cog Neil attica found that over 80% of the  time enterprises spend on AI projects goes toward   preparing cleaning and labeling data manual data  labeling is the most time-consuming and expensive   method but it may be warranted for important  applications since it can be done by anyone some   experts believe that data labeling may present  a new low-skilled job opportunity to replace   the ones that are nullified by automation  because there is an ever-growing surplus   of data and machines that need to process it to  perform the tasks necessary for advanced ml and   AI which will create more and more low-skilled  jobs and needs to hire people please leave a   like if you learn something and subscribe to the  channel to not miss any terms clearly explained

Channel: What's AI by Louis-François Bouchard

Views: 53,689

Keywords: ai, artificial intelligence, machine learning, deep learning, ml, spreadknowledgenotgerms, python, data, datascience, datascientist, introduction, beginners, datas, label, labeled, annoted, annotation, annote, annotation tool, annotation data, data annotation, data annotator, image annotation tool, image annotation tools, annotation services, annotate, annotate definition, what are annotations, what is annotation, what is data labeling, what is data annotation, how to data label, how to label

Id: lMwX-n_1NXs

Length: 3min 40sec (220 seconds)

Published: Wed Apr 29 2020