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Top News In இயந்திரம் கற்றல் மாதிரிகள் Today - Breaking & Trending Today

Finding the Great Predictors for Machine Learning

Informationweek
Finding the Great Predictors for Machine Learning
Planning a data model takes a clear look at how variables should be used. A few techniques like factor analysis can help IT teams develop an efficient means to manage a model. Here s how.
Planning machine learning models often means you discover ways to refine the number of variables that inputs data to that model. Doing so reducing your analysis times. One choice you should consider for making your analysis efficient is a factor analysis. You right choice of a factor analysis can confirm if a model can be simplified.
Image: Gorodenkoff - stock.adobe.com ....

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Smart factories keep an ear to the ground

Smart factories keep an ear to the ground
Asquared IoT’s sound analytics edge computing device Equilips (seen at top right corner) deployed at a welding station.Premium
5 min read
Asquared takes IoT into the untapped market of analyzing the sounds of machines to predict impending breakdowns
The neural network or AI brain is periodically trained with fresh data and learning captured on the edge devices
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When you take your car to a mechanic, the first thing he might do is to rev it up. The sound of the engine can tell him straight away if something’s off. ....

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Interesting Research Programs from the 2010s

The Disordered Mind Theory of Mental Illness
In a series of articles and books over the past decade, the philosopher George Graham develops a theory of mental disorder with the following qualities: 1. is non-reductionist with respect to the mind and the brain; 2. is informed by the philosophy of mind; and 3. coheres with the experiences of patients and clinicians. Grahamâs theory holds that mental illness is distinct from somatic/bodily illness though may co-occur or otherwise be bound up with so-called broken brains. A helpful analogy for what is meant here by âthe mentalâ or âthe mindâ is to view the brain as computer hardware, whereas the mind is software. On this picture, the mind and the brain are surely not independent; a hardware issue may impede the computation of some software. However, one may have bugs in oneâs software - âgumming up the worksâ to use a common phrase of Graham - on perfectly functioning hardware. ....

United States , Kevin Kelly , Kai Stinchcombe , David Atkinson , Selim Berker , Jeanne Peijnenburg , Larry Wasserman , Christoph Molnar , George Graham , Topological Properties Of Concept Spaces , Society For Exact Philosophy , Georgia State University , Practical Deep Learning , Learning Theory , Reliable Inquiry , Topological Properties , Concept Spaces , Inductive Problems , Theory Choice , Theory Change , Inductive Truth Conduciveness , Disordered Mind Theory , Abraham Dilemma , Top Books , Hearing Voices , Mental Illness ,

Understanding the Data Privacy Risks With AI-Driven AR/VR Applications | Perkins Coie

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In the 2020 Augmented and Virtual Reality Survey conducted by Perkins Coie, Boost VC, and the XR Association, nearly three-quarters of industry leaders polled indicated that they expect immersive technologies to be mainstream within the next five years. A noteworthy number of industry leaders believe that artificial intelligence (AI) and machine learning will help drive this adoption in both consumer and business segments. The growth of immersive technologies with AI and machine learning does, however, come with risks. This article will discuss the legal, compliance, and ethical risks in the data privacy landscape when integrating machine learning functionality into immersive technology offerings. ....

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