Active Learning: Why Some Data Are More Equal Than Others
Deep LearningModelingactive learningEurope 2020posted by ODSC Community September 7, 2020
This article discusses active learning and how it can help streamline the data annotation process. Artificial Intelligence is a technology that thrives on two kinds of fuel – computing power and data. Their increasing affordability is the driving force behind the recent AI boom. In fact,... Read more
Guided Labeling: Human-in-the-Loop Label Generation with Active Learning and Weak Supervision
Blogs from ODSC SpeakersConferencesMachine LearningModelingactive learningEast 2020KNIMElabelingposted by ODSC Community March 5, 2020
Paolo is a speaker for ODSC East 2020 this April 13-17. Be sure to check out his talk, “Guided Labeling: Human-in-the-Loop Label Generation with Active Learning and Weak Supervision,” at this upcoming event! One of the key challenges of utilizing supervised machine learning for real-world use... Read more
An Introduction to Active Learning
ConferencesMachine Learningactive learningsupervised learningWest 2018posted by Nathaniel Jermain July 16, 2019
The current utility and accessibility of machine learning is in part due to the exponential increase in the availability of data over time. While data is abundant, labels that are required for specific supervised machine learning tasks can be difficult to obtain. At ODSC West in... Read more
Crash Course: Pool-Based Sampling in Active Learning
Modelingactive learningMachine LearningODSC Westsupervised algorithmsposted by Spencer Norris, ODSC October 30, 2018
Active learning is a class of machine learning problems where labeled data isn’t available for supervised algorithms. Let’s take the classic setup as an example. Say we have pictures of birds and want to classify them by type, but the images don’t have labels for what... Read more