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WEBINAR: The Future of AI Marketing

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Artificial Intelligence is not about statistics, is about experience. In this webinar Stuart Waplington, Co-Founder and CEO, will walk you through what deep learning really means and the possibilities that have been unlocked to the marketing world. The global market for AI is set to be worth $5.05 Billion by 2020 (Markets & Markets). Happy Finish is already ahead of the curve; we've just presented Shoegazer, a unique Proof of Concept that uses AI and Transfer Learning to identify the exact brand and style of trainers in real-time – with 95% accuracy and Buzzteam, our on-demand workforce resource platform which allows individual companies building teams by employing global network of resources that can be discovered by skill-set, experience, cost or rating. Join this webinar to understand AI and how its rapid adoption is set to transform a range of markets, from advertising and media to finance and retail, offering benefits such as improved productivity and increased customer satisfaction.


How to improve your analytics talent

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Data Analytics is one of the most sought-after skill sets today, with students and professionals alike aspiring to be enabled with the necessary skills to derive data-driven business insights in their careers. It also helps organisations attain a competitive advantage over others. Data Analytics is not limited to mathematicians, statisticians or IT professionals with programming skills. The need to analyse data has become so elementary today that a professional in any business is expected to know the necessary skills. While professionals today are aware of the need to be trained, some are unaware of how to embark on a career in analytics.


IBM Watson Can Help Find Water Wasters In Drought-Stricken California

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Using that information, water authorities or companies can target areas or homes where people are wasting water, and send specialized educational materials to let people know how they can cut down on water waste. Some of OmniEarth's customers have already started seeing results, with some reporting a 15 percent reduction in water use, just by using the conservation messages. Many people, Fentzke said, may not even realize that they're wasting water. There could be bad meters, leaks, or bad settings on automatic sprinkling systems that are contributing to the problem. "We've found it to be very effective in targeting people who may not even know that they're inefficient," Fentzke said.


Creating a learning health system with machine intelligence

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As healthcare systems strive to realize IOM's vision for continuous improvement in care delivery, many are recognizing that they have outgrown their data management and reporting capacity. Those that have turned to new machine-learning approaches have found they can expand capacity and capabilities while reducing administrative burden on clinicians. Here's an example of how one health system used machine-learning tools to improve care delivery for intestinal surgery: Until recently, the health system's surgical services team used traditional methods of hospital data analysis to inform their creation of order sets, protocols, and provider and patient education materials spanning the pre-op, intraoperative and post-op phases of care. Then they applied a "machine intelligence" platform that pairs machine learning algorithms with topological data analysis (TDA)--a mathematical process that uses shape as an organizing principal for understanding complex data. By giving visible form to their data, the health system was able to replicate and validate years of analytical insights in a matter of days.


Digitalizing business: The difference two letters can make - TotalCIO

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Thanks! We'll email you when relevant content is added and updated. We'll email you when relevant content is added and updated. We'll email you when relevant content is added and updated. We'll email you when relevant content is added and updated. If you answer the question with another -- Does it matter?


The world's best gamers may one day compete against the smartest computers

Los Angeles Times

Google cut power usage in its data centers by several percentage points earlier this year by trusting artificially intelligent software derived from 1980s-era Atari video games. And in the years to come, the Internet giant not only could save much more electricity, but also solve far larger problems by taking on a much more complex video game. Research scientists at Google's DeepMind unit announced Friday they are developing a computer program that reads data about Blizzard Entertainment's "StarCraft II" games and learns how to play on its own. The software would have to figure out how to split its attention between micromanagement and long-term strategic decisions. It's that maneuvering that could deliver big breakthroughs.


Using TensorFlow for Object Recognition

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Our brains can comprehend things so well that it makes vision seem very easy. It doesn't take any time for a human to detect an anomaly, or identify the difference between a bus and a car, or to detect and recognize a human face, but it is incredibly hard for a computer to learn how to detect and recognize an object as easy as a human brain. In the last couple of years researchers have made tremendous progress on addressing this problem. They have come up with a solution using deep convolutional neural networks, a model which can perform hard visual recognition tasks which are close to or sometimes even better than the human brain. Convolutional Neural Networks, is a black box that constructs features we would otherwise have to handcraft ourselves, hence to create one it takes very high computing power and a lot of time.


Why automated sentiment analysis is broken and how to fix it

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One of the most difficult challenges reporting and analytics face in public relations measurement is sentiment analysis. Machines attempt textual analysis of sentiment all the time; more often than not, it goes horribly wrong. How does it go wrong? Machines are incapable of understanding context. Machines are typically programmed to look for certain keywords as proxies for sentiment.


The Designer's Guide to AI -- a $70 Billion industry by 2020

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As artificial intelligence gains popularity, designers will need to adapt. Here's how to get started. It seems like everyone wants to invest in artificial intelligence (AI). And it's not just the tech giants: USAA is using AI to protect its users from identity theft and Under Armour has connected its health app, MyFitnessPal, to IBM Watson so users can get a more thorough read of their health. AI is already a $15 billion dollar industry, according to the MIT Technology Review, with more than 2,600 companies developing their own tech, and the value of AI is reported to rise to over $70 billion by 2020. Because of AI's business opportunities, hundreds of designers in digital agencies, people who were taught to create products and services that live on the Internet, are starting to build physical products that interact with us, respond to our moods, and make decisions for us.


Machine Learning Basics - Text Analysis

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Want to take your programming skills to the next level? You've come to the right place! Machine Learning can sound daunting, but I'm here to show you how it can be a very fun and rewarding journey! This course streamlines your learning of the material and how you implement it in future projects. Machine learning brings together computer science and statistics to harness predictive power. It's a great skill to have and brings a whole new perspective to problem solving.