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Deep Learning on Graphs (Neo4j Online Meetup #41)
 
51:45
Knowledge graphs generation is outpacing the ability to intelligently use the information that they contain. Octavian's work is pioneering Graph Artificial Intelligence to provide the brains to make knowledge graphs useful. Our neural networks can take questions and knowledge graphs and return answers. Imagine: a google assistant that reads your own knowledge graph (and actually works) a BI tool reads your business' knowledge graph a legal assistant that reads the graph of your case Taking a neural network approach is important because neural networks deal better with the noise in data and variety in schema. Using neural networks allows people to ask questions of the knowledge graph in their own words, not via code or query languages. Octavian's approach is to develop neural networks that can learn to manipulate graph knowledge into answers. This approach is radically different to using networks to generate graph embeddings. We believe this approach could transform how we interact with databases. Prior knowledge of Neural Networks is not required and the talk will include a simple demonstration of how a Neural Network can use graph data. ----------------------------- ABOUT THE SPEAKER ----------------------------- Andy believes that graphs have the potential to provide both a representation of the world and a technical interface that allows us to develop better AI and to turn it rapidly into useful products. Andy combines expertise in machine learning with experience building and operating distributed software systems and an understanding of the scientific process. Before he worked as a software engineer, Andy was a chemist, and he enjoys using the tensor algebra that he learned in quantum chemistry when working on neural networks. ----------------------------- ONLINE DISCUSSIONS ----------------------------- We'll be taking questions live during the session, but if you have any before or after be sure to post them in the project's thread in the Neo4j Community Site (https://community.neo4j.com/t/online-meetup-deep-learning-with-knowledge-graphs/2963). ---------------------------------------------------------------------------------------- WANT TO BE FEATURED IN OUR NEXT NEO4J ONLINE MEETUP? ---------------------------------------------------------------------------------------- We select talks from our Neo4j Community site! https://community.neo4j.com/ To submit your talk, post in in the #projects (if including a link to github or website) or #content (if linking to a blog post, slideshow, video, or article) categories. ------------------------------------------------------------------------- VOTE FOR THE PRESENTATIONS YOU'D LIKE TO SEE! ------------------------------------------------------------------------- 'VOTE' for the projects and content you'd like to see! Browse the the projects and content categories in our community site and 'heart' the ones you're interested in seeing! community.neo4j.com
Views: 2748 Neo4j
Phanstiel Lecture: General Michael Hayden “Cold War Revival?”
 
01:04:18
Russian expansionism, cyber incursions, and mixed messages on counterterrorism objectives suggest continued instability for global security. A frequent commentator and nationally recognized authority of the subject, General Mike Hayden, former CIA director and NSA leader, explores these and other dimensions of the fragile US - Russia relationship. This lecture was sponsored by the Howard and Louise Phanstiel endowed Chair in Strategic Management and Leadership. Recorded October 20, 2017.
Yelawolf - Punk ft. Travis Barker, Juicy J
 
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Yelawolf “PUNK” feat. Juicy J & Travis Barker is Out Now! http://smarturl.it/PunkYelawolf Follow Yelawolf: http://www.yelawolf.com https://www.instagram.com/yelawolf https://www.facebook.com/yelawolf Music video by Yelawolf performing Punk. (C) 2017 Interscope Records http://vevo.ly/0FA6l9
Views: 2280897 YelawolfVEVO
WCUS 2018 Guitar Fri PM
 
03:53:18
Check out the schedule here: https://2018.us.wordcamp.org/schedule/
Views: 794 WordCamp US
Last Update: On the Nature of Omni Force
 
36:38
Hey hey, what is up guys, Jerry here one last time to give his thoughts on Omni Force, history of the show, making the show, ending Ben 10 Omni Force, and the Future of this channel, plus a few projects I'm working on. Download our free App! http://unclejerry50th.weebly.com/downloads.html Check out our Website: http://unclejerry50th.weebly.com Buy some Merch: http://unclejerry50th.spreadshirt.com Get Music that we use: http://unclejerry50th.weebly.com/downloads.html Follow us on twitter: https://twitter.com/unclejerry50th like our Facebook: https://www.facebook.com/unclejerry50th Follow us on google plus: google.com/+unclejerry50th Follow us on twitch: http://www.twitch.tv/jerry50th Follow us on Instagram: http://instagram.com/jerry50th/ Follow us on Snapchat: Jerry50th Be sure to subscribe to our gaming channel: https://www.youtube.com/channel/UC1OHbk1b67Zv0UY3nndEmbg Ben 10 Omni Force (The Show) https://www.youtube.com/channel/SWgmacCksiJCA/featured Patreon: http://www.patreon.com/Jerry50th Donate: https://streamtip.com/t/jerry50th Soundcloud: https://soundcloud.com/jerry50th This Video Includes: Jerry Jerry50th Unclejerry50th Ben 10, Ben 10 Omni Force, Omni Force, Ben 10 Omni Force Update, Omni Force Update, Ben 10 thoughts, making ben 10, ben 10 ending, ben 10 finale, ben 10 series finale, ben 10 last episode, History of ben 10, Future of Ben 10, #OneLastUpdate #Ben10OmniForce #Ben10 © of Unclejerry50th Productions comment rate subscribe
Views: 24 Unclejerry50th
Unsupervised Streaming Cyber-Analytics
 
01:29:02
The supervised learning approach to cyber-analytics has proven rather successful. However, there are challenges with this approach, including a frequent dearth of labelled data, the issue of temporal variation, and fundamentally, problems of data volume and velocity. In this talk, we describe simple unsupervised analytics intended to complement and enhance supervised methods. These approaches are based on detecting departures from normal behaviour, under a variety of definitions of normal. In particular we are concerned with streaming analytics, procedures which analyse and update on the fly, as data arrives. We describe adaptive estimation and change point methods for reasoning about a variety of objects, including multinomial distributions and Markov Chains. Examples of such methods operating on enterprise network data are provided. See more at https://www.microsoft.com/en-us/research/video/unsupervised-streaming-cyber-analytics/
Views: 1250 Microsoft Research

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