Q&A with our Tech Experts

No stupid questions here. Techopedia staff has answered many commonly asked technology questions and also assembled a number of experts who will answer your questions in basically any area of IT.

Featured Tech Experts

Sophie Ying

Product Manager at LeanTaaS

Sophie Ying is a product manager for iQueue for Operating Rooms at LeanTaaS. In her role, she has facilitated multiple customer implementations and has led the product improvement efforts on the Analyze module.Sophie has a background in data analytics and has worked with Fortune 500 companies to improve their operational performance using advanced analytics solutions. She holds a bachelor’s degree in Chemical Engineering from the University of California, Los Angeles and a master’s degree in Industrial Engineering and Operations Research from the University of California, Berkeley.

Daniel Dimov

Internet Law Expert

Dr. Daniel Dimov is an EU attorney-at-law specialized in the field of Internet law.Daniel is a fellow of the Internet Corporation for Assigned Names and Numbers (ICANN) as well as an arbiter with the Asian International Arbitration Centre.He worked as an expert for the EU Innovation and Networks Executive Agency (INEA) and did traineeships with the European Commission (Brussels), European Digital Rights (Brussels), and the Institute for EU and International law “T.M.C. Asser Institute” (The Hague).Daniel received a PhD in law from the Center for Law in the Information Society at Leiden University, the Netherlands. He has a Master's Degree in European law (The Netherlands), a Master's Degree in Law (Bulgaria), and a certificate in Public International Law from The Hague Academy of International law.Daniel has authored numerous publications in the field of Internet law.

John Graff

Practice Director, Business Transformation at Sparkhound

John Graff, PMP, is Practice Director, Business Transformation at Sparkhound, and is an experienced program manager well versed in Project Lifecycle Change Management and Project Management Agile Scrum Methodology. He is a strong leader with outstanding communication and organizational skills, and excels in driving teams to successful solutions through his ability to innovate change with visionary thinking and strategic management. John holds a Bachelor of Science from Southeastern Louisiana University.

Q&As

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The idea of applying the Internet of Things (IoT) to business intelligence (BI) is now becoming a mainstream part of corporate strategy. IoT has taken off over the past few years, and the BI industry...
Answered by: Justin Stoltzfus
Contributor, Reviewer
The answer to the question is a resounding YES. There can absolutely be too much data in a big data project.There are numerous ways in which this can happen, and various reasons why professionals...
Answered by: Justin Stoltzfus
Contributor, Reviewer
Machine learning professionals use structured prediction in a whole multitude of ways, typically by applying some form of machine learning technique to a particular goal or problem that can benefit...
Answered by: Justin Stoltzfus
Contributor, Reviewer
There are a number of ways to talk about why a confusion matrix is valuable in machine learning (ML) – but one of the simplest ways is to explain that the confusion matrix is a data...
Answered by: Justin Stoltzfus
Contributor, Reviewer
Fifth generation wireless (5G) and artificial intelligence (AI) are probably bound to generate a mutually beneficial relationship that could skyrocket both these technologies to a new level. 5G is,...
Answered by: Claudio Buttice
Data Analyst, Contributor
Finite state machines (FSMs), are computational models defined by a list of unique set states that can be only picked one by one. In a nutshell, FSMs are simple but elegant solutions to build AI...
Answered by: Claudio Buttice
Data Analyst, Contributor
Transparency is essentially important in data science projects and machine learning programs, partly because of the complexity and sophistication that drives them — because these programs are...
Answered by: Justin Stoltzfus
Contributor, Reviewer
This fundamental question about machine learning takes into account many different aspects of how these complicated programs work, and what role they play in today’s economy.One of the easiest...
Answered by: Justin Stoltzfus
Contributor, Reviewer
There are a number of reasons why the Python programming language is popular with professionals who work on machine learning systems.One of the most commonly cited reasons is the syntax of Python,...
Answered by: Justin Stoltzfus
Contributor, Reviewer
There are a number of ways to explain and define “precision and recall” in machine learning. These two principles are mathematically important in generative systems, and conceptually...
Answered by: Justin Stoltzfus
Contributor, Reviewer
The challenges of legacy migration projects are many and diverse. They depend on the scope of the migration process, for example, whether the process involves only the migration of data into a new...
Answered by: Justin Stoltzfus
Contributor, Reviewer
The use of graphics processing units (GPUs) has particular importance for the field of deep learning. The reason has to do with how deep learning systems are set up, and what they are intended to do...
Answered by: Justin Stoltzfus
Contributor, Reviewer
Businesses may invest in decision automation for any number of reasons. However, there are some overarching fundamental principles that illustrate the benefits of decision automation systems.One big...
Answered by: Justin Stoltzfus
Contributor, Reviewer
Connective intelligence is a term coined by Derrick de Kerckhove (1997) that describes a form of distributed and more evolved intelligence that goes beyond the abilities of a single user in an...
Answered by: Claudio Buttice
Data Analyst, Contributor
A variation of virtual reality (VR), augmented reality (AR) is an enhanced version of a real-world environment that superimposes or blends interactive digital elements into physical objects. Although...
Answered by: Claudio Buttice
Data Analyst, Contributor
The fundamental feature of Web 3.0 that is going improve data connection is the creation of the semantic web. Right now, albeit intelligent, machines only have a somewhat limited ability to &ldquo...
Answered by: Claudio Buttice
Data Analyst, Contributor
There are any number of complicated ways to describe bias and variance in machine learning. Many of them utilize significantly complex mathematical equations and show through graphing how specific...
Answered by: Justin Stoltzfus
Contributor, Reviewer
The fundamental interplay of threats and the intelligence with which we respond to them has not really changed. One party strives to compromise another party — by stealing goods, money or...
Answered by: Gene Yoo
Chief Executive Officer at Resecurity
Ensemble learning has various benefits for machine learning projects. Many of these are related to using a large number of relatively simple nodes to aggregate some inputs and output results.For...
Answered by: Justin Stoltzfus
Contributor, Reviewer
Fundamentally, a cyber threat intelligence analyst is someone who specializes in collecting, interpreting and understanding the significance of threat intelligence information. Unlike a security...
Answered by: Gene Yoo
Chief Executive Officer at Resecurity
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