TensorFlow 2.0 Multi-Label Clarifications with MLP

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In this article, the idea is to demonstrate how to use TensorFlow 2.0 for a multi-label classification problem. The jupyter notebook is also shared on GitHub, please find the link below. In the previous example, we demonstrated how to create a primitive neural network for a linear regression problem. However, sometimes there might be different use-cases rather than a simple linear prediction. For instance, the solution might be more complicated and difficult when we have a multi-dimensional data set for a particular problem such as a computer vision problem.


Emerging Technology and Financial Security Explore Commonwealth

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New and emerging technologies throughout history have transformed our lives, well-being, and day to day tasks. This is true in financial services as well: we use cash less and cards more, have access to banking services 24/7, and can perform most aspects of our financial lives without visiting a bank branch. Emerging technologies also carry new risks and are distributed unevenly, with some populations using cutting edge technology to get ahead, while others are left out of the system. When it comes to financial services, Commonwealth believes that it is crucial to ensure financially vulnerable consumers are included as our financial system continues to evolve. Our team focused on getting a deeper understanding of the technology and use cases for blockchain, machine learning, and data science.


The success of machine learning rests on scalability

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Instead, engineers will need to design systems that offer scalable performance, that are able to dynamically adjust the type of processing resource they deliver based on the task at hand. This is different to what embedded engineers may be comfortable with right now. For some years embedded processors have had the ability to vary their operating frequency and supply voltage based on workload. Essentially, a processor's core can run slower when it isn't busy; scaling back the main clock frequency directly translates to fewer transistors switching on and off per second, which saves power. When the core really needs to get busy, the clock frequency is scaled up, increasing the throughput.


A brief history of machine learning in cybersecurity

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David Barton is chief information security officer (CISO) at Stellar Cyber, a Silicon Valley-based security company that created the industry's first Open Detection and Response (Open-XDR) platform. Barton has more than 20 years of experience in security leadership roles across a variety of industries, including telecommunications, healthcare, software development, finance and government. He has led security operations at marquee companies including AT&T/Cingular, Sprint/Nextel, Five Iron, Forcepoint and HireRight. Barton holds an executive Master of Business Administration from the University of Missouri, Kansas City, a Bachelor of Science in management information systems from Simpson College and a CISSP certification.


Artificial intelligence: Should we be afraid? Or should we invest?

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JC2 Ventures CEO and founder and Cisco chairman emeritus John Chambers discusses the ongoing journey to 5G in the U.S. and how artificial intelligence can help or hurt the job market. With artificial intelligence quickly creeping into people's everyday lifestyle, some people are wondering if it's a technology to be feared or lauded. Former executive chairman and CEO of Cisco Systems, and now JC2 Ventures CEO and founder, John Chambers spoke to FOX Business' Liz Claman on Thursday about where he lands on that debate. "I think it's a combination of perhaps three areas," Chambers said on "The Claman Countdown." "If you're going to bet on one technology ... I'd bet on artificial intelligence."


IIeX Leadup with Sid, Nuchy and Joel

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Our third interview is with Sid Dutta of MD APAC Kantar Profiles Division, Nuchy Tungwarapojwitan of MD Intage Thailand, and Joel Vermaas of Nature Research Australia. Watch how they collaboratively share some insightful information about the future of research and how AI can change everything. For more episodes of APACInsight, make sure to subscribe to our channel. Use this code "INNOVATION30" to save 30% on your ticket.


Pratik Gandhi on LinkedIn: "Great report for individuals who want to understand technology implementation and use of #ai in education. Kudos to Bijay Dhunganaji"

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I was honoured to be part of a team of International experts who recently published UNESCO report on exploring the use of Artificial Intelligence to support teachers and teacher development: Discussion report from the International Task Force on Teachers for Education 2030's Mobile Learning Week 2019 Strategy Lab. In an effort to better understand the potential role of Artificial Intelligence (AI) in education, UNESCO Mobile Learning Week 2019 was convened to focus on the role of AI and sustainable development. As a part of this flagship event, a diverse gathering of over 40 international experts in teacher education participated in a strategy lab to explore the potential use of AI to support teachers and teacher development. Please download our report through the link below.


The Need for AI Governance in Healthcare CDOTrends

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New applications of artificial intelligence (AI) are emerging at a very fast pace, particularly in the healthcare industry. The industry is full of technology vendors, data science companies, researchers and innovators focused on creating predictive and prescriptive algorithms for improved diagnosis and treatment recommendations. By 2021, Gartner predicts that 75% of healthcare delivery organizations (HDOs) will have invested in an AI capability that is explicitly improving either operational performance or clinical outcomes. The more activity there is around using AI in healthcare, the greater the need for HDOs to establish AI governance. AI governance is necessary, especially for clinical applications of the technology.


The Apple Card algo issue: What you need to know about A.I. in everyday life

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When tech entrepreneur David Heinmeier Hansson recently took to Twitter saying the Apple Card gave him a credit limit that was 20 times higher than his wife's, despite the fact that she had a higher credit score, it may have been the first major headline about algorithmic bias you read in your everyday life. It was not the first -- there have been major stories about potential algorithmic bias in child care and insurance -- and it won't be the last. The chief technology officer of project management software firm Basecamp, Heinmeier was not the only tech figure speaking out about algorithmic bias and the Apple Card. In fact, Apple's own co-founder Steve Wozniak had a similar experience. Presidential candidate Elizabeth Warren even got in on the action, bashing Apple and Goldman, and regulators said they are launching a probe.


AI and Medical Diagnosis

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In the golden age of Artificial Intelligence, healthcare is the new frontier of research and development. Surgeons are routinely using robotic assists to operate with less invasiveness and more precision. Gene sequencing and gene editing aided by AI is transforming the way scientists obtain cures for diseases. But, most notably, research is underway to allow AI to transform the way doctors diagnose patients. You have symptoms of a cold.