Unsupervised learning

DataVisor Defines the Future of Digital Fraud and Risk Management With Next-Gen Platform Capabilities

Retrieved on: 
Tuesday, November 29, 2022
Banking, Software, Mobile, Wireless, Networks, Professional Services, Internet, Fintech, Data Management, Technology, Artificial Intelligence, Security, Finance, Other Technology, Uis, Organization, Attack, Machine learning, Risk, Galileo Galilei, Enrichment, Cloud computing, Fortune 500, Software as a service, Unsupervised learning, ML, Fraud, Equifax, Mastercard, Intelligence, Risk management, ROI, Online shopping, Map

DataVisor Fraud Platform, together with these enhanced capabilities and its innovative approach using Unsupervised Learning, delivers complete protection in a single, powerful cloud-based SaaS solution.

Key Points: 
  • DataVisor Fraud Platform, together with these enhanced capabilities and its innovative approach using Unsupervised Learning, delivers complete protection in a single, powerful cloud-based SaaS solution.
  • The ever-expanding digital footprint necessitates the use of data intelligence and signals from different attack vectors effectively and efficiently.
  • To this effect, the platform approach is at the center of transforming the approach to managing digital fraud and risk, said Yinglian Xie, Co-founder and CEO at DataVisor.
  • DataVisor is the worlds leading fraud and risk management platform that enables organizations to respond to fast-evolving fraud attacks and mitigate risks as they happen in real time.

Foyer Insight Incorporates AI and Unsupervised Machine Learning Into Unprecedented Multi-Classification Tool

Retrieved on: 
Tuesday, February 9, 2021
Cybernetics, Articles, Academic disciplines, Science and technology, Learning, Machine learning, Artificial intelligence, Estate agent, Unsupervised learning

Foyer Insight is built to easily gain a wealth of knowledge and data from images within real estate listings.

Key Points: 
  • Foyer Insight is built to easily gain a wealth of knowledge and data from images within real estate listings.
  • "With unsupervised learning as the foundation, Foyer Insight evens the playing field for real estate agents and enables them to offer clients a more robust home buying experience.
  • Through the use of AI and machine learning, Foyer Insight makes the data collected more actionable, and helps agents enhance and improve their clients' experiences during the home buying process," said Cowan.
  • Headquartered in Trumbull, CT, Foyer's elite team of AI developers have pushed unsupervised machine learning and multi-classification tools to a new level.

Machine Learning and Speech: A Review of FPF’s Digital Data Flows Masterclass

Retrieved on: 
Friday, December 18, 2020
Articles, Academic disciplines, Learning, Artificial intelligence, Emerging technologies, Artificial neural networks, Machine learning, Deep learning, Unsupervised learning, Supervised learning, Machine translation, Semi-supervised learning

Authors: Hunter Dorwart, Caroline Hopland, and Rob van Eijk On Wednesday, December 9, 2020, FPF hosted a Digital Data Flows Masterclass on Machine Learning and Speech.

Key Points: 
  • Authors: Hunter Dorwart, Caroline Hopland, and Rob van Eijk On Wednesday, December 9, 2020, FPF hosted a Digital Data Flows Masterclass on Machine Learning and Speech.
  • The masterclass on Machine Learning and Speech is the first masterclass of a new series after completing the VUB-FPF Digital Data Flows Masterclass series with eight topics.
  • Dr. Prem Natarajan (VP, Alexa AI-Natural Understanding) guides us through the intricacies of Machine Learning in the context of voice assistants.
  • The presenters explored the differences between supervised, semi-supervised, and unsupervised machine learning (ML) and the impact of these recent technical developments on machine translation and speech recognition technologies.
  • Machine Translation An Introduction As a sub-field of computational linguistics, machine translation studies the use of software to translate text or speech from one language to another.
  • Deep learning requires very large datasets and paired translation examples (e.g., English to French), which might not exist for certain languages.
  • Even when there is a large pool of data, sentences often have multiple correct translations, which poses additional problems for machine learning.
  • How to Train a Machine Learning Model Supervised, Unsupervised, and Semi-Supervised Learning Training neural models with limited translation data poses multiple problems (see also, Figure 1).
  • Finally, semi-supervised learning combines elements of both supervised and unsupervised learning and is the primary training method for translation models.
  • From a high level perspective, neural models employing machine learning produce more fluent translations than older statistical models.
  • Machine Learning and Speech Many of the lessons learned in recent advancements of machine translation also apply to the area of speech recognition.
  • Yet while the idea of machine learning through neural networking became widespread in the discipline, the lack of computing power and data inhibited its development.
  • Advancements in Training Models Indeed, present speech recognition technology utilizes a range of learning methods at the cutting edge of deep learning, including active learning, transfer learning, semi-supervised learning, learning to paraphrase, self-learning, and teaching AI.
  • Transfer learning data takes data rich domains and finds ways to transfer learning to new domains that lack corresponding data.
  • Digital Data Flows Masterclass Archive The Digital Data Flows Masterclass Archive with the recordings and resources for previous classes can be accessed here.

Leonardo247 Secures Machine Learning Patent to Identify Code Compliance Issues

Retrieved on: 
Wednesday, December 2, 2020
Data management, Technology, Residential Building & Real Estate, Software, Construction & Property, Building Systems, Articles, Cybernetics, Emerging technologies, Science and technology, Learning, Machine learning, Academic disciplines, Unsupervised learning, Artificial intelligence

10,867,135) that gives Leonardo247 rights to a process of using expert knowledge combined with limited data to "jumpstart" a machine learning (ML) algorithm that reduces the time necessary to achieve accurate ML output.

Key Points: 
  • 10,867,135) that gives Leonardo247 rights to a process of using expert knowledge combined with limited data to "jumpstart" a machine learning (ML) algorithm that reduces the time necessary to achieve accurate ML output.
  • Leonardo247 uses this artificial intelligence (AI) to translate municipal codes into actionable maintenance compliance tasks to ensure adherence to applicable laws.
  • "This patent validates our unique code compliance engine and further differentiates our offering and competitive advantage in the market."
  • However, Leonardo247's newly developed technology uses an intelligent initial data set and limited supervised machine learning to dramatically speed up the unsupervised machine learning process.

Leaders Discuss how to Detect and Prevent Fraud in Your Business

Retrieved on: 
Wednesday, September 2, 2020
Cybernetics, Learning, Machine learning, Unsupervised learning

NEW YORK, Sept. 2,2020 /PRNewswire/ --COVID19 allows businesses to take a deep breath and reassess the health of one's business.

Key Points: 
  • NEW YORK, Sept. 2,2020 /PRNewswire/ --COVID19 allows businesses to take a deep breath and reassess the health of one's business.
  • TIE, Alexis Networks and Alliance Payments Solutions have teamed up to do a first ever webinar explaining why as a business owner it's imperative to understand, detect, and prevent fraud.
  • Alliance has over 300 clients and been in business since 2006 and a premiere payments company.
  • Alexis Networks comes with API integrations for business applications and is the first in the industry with unsupervised machine learning technology.

North American Artificial Intelligence in Diagnostics Market 2020-2026 - ResearchAndMarkets.com

Retrieved on: 
Wednesday, September 2, 2020
Software, Technology, Health, Medical devices, Rare diseases, Nervous system, Articles, Neurological disorder, Organ systems, Amyotrophic lateral sclerosis, Pathology, Machine learning, Radiology, Unsupervised learning

The "North America Artificial Intelligence in Diagnostics Market By Diagnosis Type (Radiology, Oncology, Neurology, Cardiology, Chest & Lungs, Pathology and Other Diagnosis Types), By Component (Services, Software and Hardware), By Country, Industry Analysis and Forecast, 2020-2026" report has been added to ResearchAndMarkets.com's offering.

Key Points: 
  • The "North America Artificial Intelligence in Diagnostics Market By Diagnosis Type (Radiology, Oncology, Neurology, Cardiology, Chest & Lungs, Pathology and Other Diagnosis Types), By Component (Services, Software and Hardware), By Country, Industry Analysis and Forecast, 2020-2026" report has been added to ResearchAndMarkets.com's offering.
  • Degenerative neurological disorders such as amyotrophic lateral sclerosis (ALS) can be devastating to the patient.
  • Machine learning comprises a number of techniques, such as machine learning, supervised learning, unsupervised learning, and advanced learning.
  • The market research report covers the analysis of key stakeholders of the market.

Frost Radar™: User and Entity Behaviour Analytics Based on Machine Learning, 2020

Retrieved on: 
Monday, August 17, 2020
Articles, Computer security, Cybernetics, Formal sciences, Machine learning, Computer network security, Threat, Unsupervised learning, Artificial intelligence, Analytics, Network security, Security information and event management

SIEM tools can be bypassed by advanced attackers with relative ease, and focus more on real-time threats than extended attacks.User and entity behaviour analytics (UEBA) is a vital component of any SIEM system.

Key Points: 
  • SIEM tools can be bypassed by advanced attackers with relative ease, and focus more on real-time threats than extended attacks.User and entity behaviour analytics (UEBA) is a vital component of any SIEM system.
  • By combining both solutions, companies gain the benefits of threat detection techniques that examine both human and machine behaviour.
  • Artificial intelligence techniques, including supervised and unsupervised machine learning, are applied to data from network security infrastructure.
  • Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

DataVisor Named a Leader in IDC MarketScape: Worldwide Enterprise Fraud Management in Banking 2020 Vendor Assessment

Retrieved on: 
Wednesday, July 8, 2020
Consulting, Data management, Professional services, Technology, Software, Articles, Cybernetics, Academic disciplines, Learning, Machine learning, Fraud, Unsupervised learning, Artificial intelligence

DataVisor, the leading fraud detection company with solutions powered by transformational AI technology, today announced that it has been recognized as a leader in the just-released IDC MarketScape: Worldwide Enterprise Fraud Management in Banking 2020 Vendor Assessment.

Key Points: 
  • DataVisor, the leading fraud detection company with solutions powered by transformational AI technology, today announced that it has been recognized as a leader in the just-released IDC MarketScape: Worldwide Enterprise Fraud Management in Banking 2020 Vendor Assessment.
  • DataVisor was honored for its next-generation fraud detection platform, which leverages unsupervised machine learning (UML) to identify fraud in real time, focusing on account-level activity and transactions.
  • Were excited to be named a leader in IDCs Marketplace assessment, said Yinglian Xie, CEO and Co-Founder, DataVisor.
  • The recognition underscores our commitment to helping organizations leverage machine learning techniques for continuous, effective fraud protection across the account lifecycle.

Australian-based AI Company, Flamingo Ai, Granted Patent for Machine Learning Technology

Retrieved on: 
Monday, January 27, 2020
Articles, Machine learning, Cybernetics, Academic disciplines, Cognition, Emerging technologies, Artificial intelligence, Computational neuroscience, Unsupervised learning, Supervised learning

This patent sets out the algorithms that Flamingo Ai uses for the semi-supervised machine learning engine to propagate answer weights around a question space.

Key Points: 
  • This patent sets out the algorithms that Flamingo Ai uses for the semi-supervised machine learning engine to propagate answer weights around a question space.
  • Dr Jack Elliott, the inventor of the technology, notes: "Flamingo Ai's conversational intelligence relies on a novel form of semi-supervised machine learning.
  • Flamingo Ai built its own AI engine to overcome traditional AI technology challenges such as the need for large data sets, a high level of human intervention, the use of either only supervised or unsupervised machine learning approaches and 'black box' AI.
  • Founder and Executive Director, Dr Catriona Wallace stated "Flamingo Ai set out to build unique IP related to semi-supervised machine learning that would be beneficial to our customers.

DeLTA 2020: 1st International Conference on Deep Learning Theory and Applications (Paris, France - July 8-10, 2020) - ResearchAndMarkets.com

Retrieved on: 
Tuesday, January 21, 2020
Technology, Data management, Articles, Computing, Digital technology, Formal sciences, Big data, Technology forecasting, Transaction processing, Deep learning, Analytics, Unsupervised learning, Data analysis, Data science

The "DeLTA 2020: 1st International Conference on Deep Learning Theory and Applications" conference has been added to ResearchAndMarkets.com's offering.

Key Points: 
  • The "DeLTA 2020: 1st International Conference on Deep Learning Theory and Applications" conference has been added to ResearchAndMarkets.com's offering.
  • Deep Learning and Big Data Analytics are two major topics of data science, nowadays.
  • A key benefit of Deep Learning is the ability to process these data and extract high-level complex abstractions as data representations, making it a valuable tool for Big Data Analytics where raw data is largely unlabeled.
  • Deep learning approaches, leveraging on big data, are outperforming state-of-the-art more classical supervised and unsupervised approaches, directly learning relevant features and data representations without requiring explicit domain knowledge or human feature engineering.