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iPR Software Introduces the First Artificial Intelligence Application for Online Newsrooms and Digital Publishing

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LOS ANGELES, CA, Oct. 20, 2019 (GLOBE NEWSWIRE) -- via NEWMEDIAWIRE – iPR Software, the leader in Online Newsrooms, Digital Publishing, Digital Asset Management (DAM) solutions, and customized integrated solutions, announced its largest technology rollout to date at Public Relations Society of America's International Conference in San Diego, California. With the launch of "Metatron," iPR Software's new application empowers Artificial Intelligence (AI) cloud capabilities as well as integrating the power of machine learning into DAM and customized software platforms to increase productivity and corporate asset sharing across multiple customer ecosystems. This latest software release further advances the company's vision for clients to publish their news and information to Traditional and Social media channels and better engage their B2B & B2C audiences while increasing traffic to their branded media and corporate assets. Leading organization's today are utilizing cloud applications to access the latest technology with encryption algorithms they can securely manage, publish, and share rich branded media content. Metatron introduces core, cloud-based software features that enable customers to securely publish and share key digital media and corporate assets, target practical enterprise use cases, increase workflow efficiencies, and automate mundane tasks to reduce data and storage errors.


Decision Tree Classifier from Scratch: Classifying Student's Knowledge Level

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In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised classification problems. Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision. You can learn more about Decision Tree from here. We are going to use a Machine Learning algorithms to find the patterns on the historical data of the students and classify their knowledge level, and for that we are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language. Though i am going to explain everything along the way, it will not be a basic level explanation.


A Primer on Machine Learning and Deep Learning for Educators

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The field of learning has evolved drastically over the years. With the advent of e-learning and learning management systems, the process of learning has gone beyond the traditional model of classroom training. Now it is possible for instructors and teachers to reach a wider, international audience through online courses hosted on cloud based LMS platforms. Students can access these courses from any place in the world at any time, by simply logging into their account using their login credentials. Although e-learning is a complete and self-sustainable medium for imparting knowledge, it also works well in conjunction with traditional classroom training.


4 Errors of machine-learning startups - Asume Tech

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Have you heard about the Darwin Awards? Jump on YouTube and have a look. It's a naughty honor that sets people up for the most sophisticated attempts to do something they think is cool. One is taking a selfie with a wounded bear, another is screwing an engine to a skate. These bold actions lead to serious mistakes with serious consequences and funny comments.


AI, big data and the future of humanity

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"We are probably one of the last generations of homo sapiens." Those were the opening words of acclaimed historian and best-selling author Professor Yuval Harari, who spoke at the World Economic Forum Annual Meeting in Davos, Switzerland, where politicians, thought leaders and executives from the world's leading companies congregate to discuss solutions to global challenges. What comes after us, Harari said, are entities that are more different from us than we were from our predecessors, the Neanderthals. However, those species will not be the outcome of the organic evolution of human genes, Harari explained, but the outcome of humans learning to engineer bodies, brains and minds. "This will be the main product of the economy of the 21st century."


Knowing Your Neighbours: Machine Learning on Graphs

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We live in a connected world and generate a vast amount of connected data. Social networks, financial transaction systems, biological networks, transportation systems and a telecommunication nexus are all examples. The paper citation network displayed in Figure 1 is another example of connected data. Representing connected data is possible using a graph data structure regularly used in Computer Science. In this article, we will provide an introduction to the assorted types of connected data, what they represent, and the challenges we can solve.


Retool AI to forecast and limit wars

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Armed violence is on the rise and we don't know how to stop it1. Since 2011, conflicts worldwide have killed up to 100,000 people a year, three-quarters of whom were in Afghanistan, Iraq and Syria. The rate of major wars has decreased over the past few decades. But the number of civil conflicts has doubled since the 1960s, and terrorist attacks have become more frequent in the past ten years. The nature of conflict is changing.


Risks And Rewards For AI Fighting Climate Change

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As artificial intelligence is being used to solve problems in healthcare, agriculture, weather prediction and more, scientists and engineers are investigating how AI could be used to fight climate change. AI algorithms could indeed be used to build better climate models and determine more efficient methods of reducing CO2 emissions, but AI itself often requires substantial computing power and therefore consumes a lot of energy. Is it possible to reduce the amount of energy consumed by AI and improve its effectiveness when it comes to fighting climate change? Virginia Dignum, an ethical artificial intelligence professor at the Umeå University in Sweden, was recently interviewed by Horizon Magazine. Dignum explained that AI can have a large environmental footprint that can go unexamined.


8 AI Diagnostics and Imaging Startups for Digital Health

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Investing in emerging technologies can be extremely risky. It can also be extremely rewarding – and not just for your bank account. Technologies like artificial intelligence have the potential to change the world in many different ways. One of the industries where AI is already making real advances is healthcare, such as the ability to design and validate drug candidates to treat disease in less than two months. That has attracted the attention of plenty of deep-pocketed investors into AI healthcare startups, which have made more deals than any other AI industry since 2014, according to research firm CB Insights, with more than 80 AI diagnostics and medical imaging companies leading the way across 150 deals and counting.


Data Science's Most Misunderstood Hero

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Be careful which skills you put on a pedestal, since the effects of unwise choices can be devastating. In addition to mismanaged teams and unnecessary hires, you'll see the real heroes quitting or re-educating themselves to fit your incentives du jour. A prime example of this phenomenon is in analytics. The top trophy hire in data science is elusive, and it's no surprise: "full-stack" data scientist means mastery of machine learning, statistics, and analytics. When teams can't get their hands on a three-in-one polymath, they set their sights on luring the most impressive prize among the single-origin specialists. Today's fashion in data science favors flashy sophistication with a dash of sci-fi, making AI and machine learning darlings of the hiring circuit.