Google Analytics is a gold mine of data, and the backbone of many digital marketing processes. Google's adding in a new natural language query process which will help users find relevant insights quickly and easily. Last September, they added Automated Insights which aims to highlight relevant fluctuations and changes in your Google Analytics data to help keep you on top of all the important measurements. Google does say that the system may not be able to answer all of these queries, as it depends on the surrounding context, but they are working to improve and upgrade the system based on use.
Faced with growing costs for extraction and processing and increasing competition, mine operators are turning to advanced technology tools to speed the discovery of mineral deposits. For Goldcorp, these tools now include cognitive technology from IBM applied to multiple information sources to help geologists locate high-value exploration targets faster and with greater accuracy, thereby reducing extraction costs and environmental impact. According to Mark Fawcett, partner, IBM global business services and project lead, Goldcorp's Watson initiative was a collective effort that drew on the strengths of both the IBM and Goldcorp organizations in the implementation and training of the Watson system. The gold in any analytics project, the Red Lake project began with the collection of information resources, including structured and unstructured data.
A gold mining company -- Newcrest Mining -- provided operating data for a number of its plants, with the aim that some of the teams attending could provide useful solutions grounded in Data Science. To keep autoclave sizes and capital costs down, Newcrest's autoclaves instead rely on purified oxygen, provided by an air separation unit (ASU). This presents an opportunity to minimise the excess oxygen and therefore reduce ASU electricity consumption -- saving money and reducing GHG emissions. The variables included temperature measurements, ore flow rate, and operating pressure.
This type of data is often referred to as alternative data, and with the ever-increasing levels of data available in the modern world comes the opportunity to gain unique insights, competitive industry advantage, and boosted profits. The CEO of Foursquare, which is a search-and-discovery service mobile app, predicted a 30% drop in Q1 sales for Chipotle, based on footfall data accumulated by their app users. These three examples show alternative data being sourced from a social app, email receipts and satellite imagery, highlighting the breadth and variety of potential sources that can be explored.
As customers consume managed services offered by the cloud platform, they generate additional data which becomes a gold mine for cloud providers. The bottom line is that the cloud has all essential components – ample compute power, abundant storage backend, massive amount of data - to deliver compelling Machine Learning capabilities. In the recent past, top cloud providers including Amazon, Google, IBM, Microsoft, and Salesforce started to emphasize on cognitive computing and intelligent cloud. The next generation cloud powered by Machine Learning will offer services for building applications based on cognitive computing, predictive analytics, intelligent Internet of Things, interactive personal assistants and bots.
Wynn Las Vegas set the tone last month for the types of technology trends the industry might see going forward by announcing that all 4,748 guest rooms at Wynn Las Vegas and Encore will be equipped with Amazon Echo -- Amazon's artificial intelligence device -- by this summer. Speaking Wednesday on CES 2017 tech trends to a packed room of about 500 at the Las Vegas Convention Center, DuBravac said voice recognition and artificial intelligence will be a a recurring theme on the show floor. "Voice recognition, whether it's Amazon's Alexa or other things, makes a lot of sense in hotel rooms, where you may not know where the light switch is, you may not know how to close the blinds -- we can now add some level of automation that can drastically improve the consumer experience," DuBravac told the Review-Journal. "They see how the world is changing, how digitization, sensorization, artificial intelligence and voice are starting to impact the type of experiences that we have," DuBravac said.
But your snapshots are also a potential gold mine of information about what you spend money on for those sites and the companies that advertise on them. Artificial intelligence software is on the horizon that can spot brands like Nike or Coke even in images without text or tags. In general the software winning these investments uses machine vision, image recognition and/or visual search algorithms to identify objects and shapes as well as textures. One startup called Ditto Labs makes a search engine that specifically examines digital images for logos and brands.
This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naïve Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.
Just like Google can build a highly accurate spam filter to keep you from wasting time on the pleas of Nigerian princes, deep learning can classify text by many measures, including its degree of factuality, falsehood or truthiness. Just like Google can build a highly accurate spam filter to keep you from wasting time on the pleas of Nigerian princes, deep learning can classify text by many measures, including its degree of factuality, falsehood or truthiness. Then we can perform powerful mathematical operations on text to detect patterns and similarities, make predictions and apply categories to it. While media endorsements meant diddly squat this election cycle, the way that media and social media promoted false stories week after week to increase their eyeballs and mindshare had a huge effect.