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List of Top 10 Machine Learning Examples in Real Life

Openxcell

But with technological progress, machines also evolved their competency to learn from experiences. This buzz about Artificial Intelligence and Machine Learning must have amused an average person. But knowingly or unknowingly, directly or indirectly, we are using Machine Learning in our real lives.

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Understanding Bias in Artificial Intelligence

TechFides Blog

With the mad rush to apply Artificial Intelligence capability to almost every square inch of our daily lives, it is absolutely critical to be cognizant of the types of bias that are inherent in the existing AI models. ” Consider your experience with information on the internet over the past 25-30 years.

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Many users across many platforms make for a uniquely large attack surface that includes content fraud, account fraud, and abuse of terms of service. Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. The features mainly belong to two distinct classes.

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Artificial Intelligence 101: What It Is, Its Evolution and Potential Jobs

Apiumhub

Artificial Intelligence 101 has become a transformative force in many areas of our society, redefining our lives, jobs, and perception of the world. AI involves the use of systems or machines designed to emulate human cognitive ability, including problem-solving and learning from previous experiences.

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Highlights from the O’Reilly Artificial Intelligence Conference in London 2019

O'Reilly Media - Data

People from across the AI world came together in London for the Artificial Intelligence Conference. Raffaello D’Andrea presents his vision of how autonomous indoor drones will drive the next wave of robotics development. Ben Lorica and Roger Chen review how companies are building AI applications today.

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

Netflix Tech

In this blog post, we present our project on Auto Remediation, which integrates the currently used rule-based classifier with an ML service and aims to automatically remediate failed jobs without human intervention. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

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Reducing Blind Spots in Cybersecurity: 3 Ways Machine Learning Can Help

Tenable

Faced with an expanding attack surface and limited resources, security teams can apply machine learning to prioritize business risks and help predict what attackers will do next. Machine learning helps security teams work smarter. In today’s cybersecurity landscape, gaps in your visibility are inevitable.