Machine-Learning

Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data.For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages. After learning, it can then be used to classify new email messages into spam and non-spam folders.The core of machine learning deals with representation and generalization. Representation of data instances and functions evaluated on these instances are part of all machine learning systems.
Posts about Machine-Learning
    • 2017: The Year of Machine Learning, Intelligent Content and Experiences

      It is common knowledge that the amount of information available in the digital ecosystem is exploding. By 2020 it is expected to have grown from 130 exabytes to 40,000 exabytes. Digital (and in our case search and content) data holds the keys to marketing success. It contains the critical patterns on consumer intent and behavior, preferences, and content/topics that brands nee ...

      Jim Yu/ Search Engine Watchin Content- 8 readers -
  • The natural evolution of digital for brands: becoming more human

    … intelligence is now embedded across platforms and services, harnessing intent understanding and using a vast base of semantic knowledge. When coupled with machine learning that’s infused throughout all of our digital interactions, technology is becoming more human. People and machines are able to sustain conversations with personal digital assistants…

    Search Engine Watch- 8 readers -
  • How does RankBrain work and what does it mean for search marketers?

    … It’s hard to meet anyone in the digital industry who hasn’t heard about RankBrain. And it comes as no surprise that this system along with its impact on search results raises endless questions and disputes. We’ve made an attempt to understand the way RankBrain operates and if there’s anything we can possibly do to optimize for it. Let’s start…

    Search Engine Watchin How To's- 7 readers -
  • How content marketers and SEO experts can optimize for RankBrain

    … Google’s search engine deliver more appropriate results then your content should have the following: Answer problems your target audience are having and may search for solutions online. Your content should cover the topics ultimately including references and supporting information Dump keyword focusing and include a natural language…

    Search Engine Watch- 10 readers -
  • Understanding intent through voice search

    … It’s search Jim, but not as we know it. The dream of an ultimate personal assistant isn’t a farfetched sci-fi fantasy like the interactive computing systems in Star Trek. It’s technology available today already being applied to search engines. Leading visionaries in search technology, including Google’s Beshad Behzadi in his keynote speech…

    Search Engine Watch- 10 readers -
  • Can artificial intelligence save social?

    … on this, because it’s going to be increasingly important in the next year), but until platforms themselves start integrating this technology efficiently then we’re going to have a rocky ride. I certainly don’t pretend to have all the answers (or even all of the questions), but it feels to me that if we can capture and connect community content using deep learning machines, then social will have a real future, rather than becoming a digital echo of older broadcast models. …

    Matt Owen/ Search Engine Watchin Social- 14 readers -
  • For AKQA, creative display is essential to brand campaigns

    …, componentized with machine-learning data decisioning pushing this all along. Google has a lot of interest in this. They’re already auto-translating Flash into HTML for mobile. How close to you think the industry is to seeing your wish come true? There are only a few vendors trying to solve these things. We see companies like Celtra and Google…

    Digiday- 18 readers -
  • Vladimir Vapnik Joins Facebook AI Research

    … the capacity of a learning machine. Vladimir is rejoining some of his long-time collaborators: Jason Weston, Ronan Collobert and Yann LeCun. He is working on a new book and will be collaborating with FAIR (Fundamentals of Artificial Intelligence Research) research scientists to develop some of his new ideas on conditional density estimation, learning with privileged information and other topics. According to VentureBeat, Vapnik, Weston, Collobert and LeCun worked together at AT&T. …

    David Cohen/ AllFacebookin Social- 6 readers -
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