Breaking News

Unsupervised Learning: An Overview on Emerging Machine Learning/Artificial Intelligence Approaches – GlobeNewswire

Dublin, Sept. 02, 2020 (GLOBE NEWSWIRE) — The “Towards Being Truly Intelligent: Next Wave of AI Technologies (Wave 1 – Unsupervised Learning)” report has been added to’s offering. As industries across the globe pursue digitization across functions, more and more data are being generated and utilized to empower decision-making and insight generation. As the volume and complexity of data increases, it is also becoming difficult for traditional machine learning (ML) algorithms to make sense of a large number of variables. The labeling and annotation of such large and complex datasets are highly laborious and time-consuming, making ML unscalable. While most of the current ML-based systems depend largely on supervised ML algorithms, unsupervised learning (UL) systems after years of theoretical and lab research have found applicability in commercial applications and have been at the center of many initiatives in industries such as automotive, finance, and cybersecurity. In brief, this research service covers the following points: Introduction to Unsupervised LearningApplications of Unsupervised LearningInnovators and InnovationsGrowth Opportunities Key Topics Covered: 1.0 Executive Summary1.1 Research Scope1.2 Research Methodology 2.0 Unsupervised Learning – Introduction2.1 Unsupervised Learning Lays the Framework for Truly Automated Machine Learning Where Human Intervention Is Minimal2.2 Unsupervised Learning Works Accurately with Large Datasets Which Cannot be Labeled Manually2.3 Clustering of Data into Groups Makes Them More Suitable and Understandable for Further Analysis2.4 A Variety of Data Clustering Methods Based on Unsupervised Learning can be Used Based on the Type of Dataset and the Objectives2.5 Dimensionality Reduction Techniques Play a Key Role in Prepping up Large Datasets for Analysis2.6 Autonomy and Minimal Human Intervention in Unsupervised Learning Systems Create Ambiguity in Output 3.0 Innovations and Companies to Action3.1 Unsupervised Learning Will Empower a Higher Level of Autonomy Among Self-driving Cars3.2 Unsupervised Learning can Help NLP Systems Learn More Easily and Rapidly with Unknown Languages and Accents3.3 Unique Financial Frauds with no Precedent can Be More Accurately Identified with Unsupervised Learning Methods3.4 Identifying Outliers From Datasets Is a Key Strength of UL Systems, Making Them Fit for Detecting Malicious Behavior3.5 Cybersecurity is Emerging as a Key Area of Innovation for Unsupervised Learning 4.0 Growth Opportunity4.1 Pursuit of Greater Degree of Autonomy Among Self-driving Cars Is Facilitating the Adoption of Unsupervised Learning Techniques4.2 The Accuracy of Artificial Intelligence System Is Highly Dependent on the Quality of Training Data Used to Train Algorithms4.3 Industry-academia Collaborations can Accelerate the Pace of Commercial Adoption of Unsupervised Learning 5.0 Industry Contacts5.1 Key Contacts For more information about this report visit About is the world’s leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends. Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research. CONTACT:
Laura Wood, Senior Press Manager
[email protected]
For E.S.T Office Hours Call 1-917-300-0470
For U.S./CAN Toll Free Call 1-800-526-8630
For GMT Office Hours Call +353-1-416-8900