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Computer Science
Cybersecurity

Machine Learning Based on Cloud Solutions

Profile image of Przemysław ChmieleckiPrzemysław Chmielecki

2019, Edukacja – Technika – Informatyka

https://doi.org/10.15584/ETI.2019.1.17
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7 pages

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Abstract

Cognition is a domain of thinking creatures, isn't it? Based on that computers cannot learn anything more than was in the initial data feed. In this article, I just want to defend that nowadays technical solutions can break this rule. The aim of this article is to provide a short technical overview what Machine Learning (ML), Artificial Intelligence (AI) and Neural Networks (NN) were before in the area of standalone gigantic servers, and how do they look now in Cloud Computing (CC) times. The ML paradigm is not any more reserved for big enterprises only but now is available for single internet user. I just want to present AWS and Azure, as the biggest CC providers, functionalities and potential usage of such Cognitive Services (CS) in current internet services. The great example is for instance bot usage instead of diving deep in the FAQ on the company website or digging into the corporate wiki. Another big area is graphics analysis and sound or text recognition. Those are only examples of predefined CC functions ready for use right now in the public cloud.

FAQs

sparkles

AI

What key trends are shaping the future of machine learning technologies?add

The trends indicate significant growth in Deep Learning and Virtual Assistants over the next 2-10 years, as highlighted in the 2017 Gartner Hype Cycle.

How has the shift to cloud computing impacted machine learning infrastructure?add

The shift to cloud computing simplifies ML usage, allowing developers to utilize services like AWS and Azure without extensive infrastructure management.

What distinguishes reinforcement learning from traditional machine learning approaches?add

Reinforcement Learning focuses on learning through environmental interaction and feedback rather than relying solely on labeled training data, allowing for adaptation over time.

How do Microsoft Azure and AWS differ in their machine learning service offerings?add

While Azure offers services like Face API and Emotion API, AWS provides solutions such as Amazon Rekognition and Amazon Comprehend, catering to various AI needs.

What evidence supports the effectiveness of machine learning in email spam detection?add

Spam detection, exemplified by Google's SpamAssassin, utilizes Bayesian classification filters, learning from user input to continually improve classification accuracy over time.

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