rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deep Learning
  name:
    name part: O'Reilly Media, Inc.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: moving image
  genre: videorecording
  genre: Electronic videos.
  origin info:
    place:
      place term: xx
    date issued: 2015
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 video file, approximately 2 hr., 3 min.)
  abstract: Push the envelope of data science by exploring emerging topics such as neural networks, deep learning, speech recognition, and visual intelligence with this video collection, taken from the Hardcore Data Science sessions at Strata + Hadoop World conferences in 2014 and 2015. This video collection includes: Neural Networks for Machine Perception Ilya Sutskever (Google Inc) Learn what neural networks are, how they work, and how they helped achieve the recent record-breaking performance on speech recognition and visual object recognition. Beyond DNNs towards New Architectures for Deep Learning, with Applications to Large Vocabulary Continuous Speech Recognition Tara Sainath (Google) Tara presents the latest improvements in deep neural networks (DNNs), including alternative architectures such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs). A Quest for Visual Intelligence in Computers Fei-Fei Li (Stanford University) Look into computer vision technology, including ongoing projects in large-scale object recognition and visual scene story telling from Stanford Vision Lab. Building and Deploying Large-scale Machine Learning Pipelines Using the Berkeley Data Analytics Stack Ben Recht (University of California, Berkeley) Focus on scalable computational tools for large-scale data analysis, statistical signal processing, and machine learning. Ben explores the intersections of convex optimization, mathematical statistics, and randomized algorithms.
  note: O'Reilly Media, Inc..
  note: Videorecording.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781491931011
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 170615
    record change date: 20260129163204.9
    record identifier: in00004099722