deep-learning-with-keras-shubhabrata-roy.json

{
  "description": "It has always been our dream to create machines that can think. In the\nearly phase of artificial intelligence, we solved the problems that\ncould have been described by a list of formal and mathematical rules.\nThe main motivation was solving the tasks that are trivial for people to\nperform but difficult to describe formally, for example recognizing\nobjects in images or spoken words. Neural networks have been one\npredominant area of research in artificial intelligence that stayed in\nlimelight over the past five decades or so. However, one major boost in\nthis domain happened around 2010 when the computers got much faster and\ndata sets got much bigger. The existing algorithms with some critical\ntweaks and improvements became much more efficient and won several\nchallenges in computer vision, speech recognition, and natural language\nprocessing. In this talk, I would briefly describe how neural networks\nworks and then move towards state-of-the-art approaches of deep\nlearning. I would describe in detail how to build deep learning models\nand its training procedures using the deep learning library \"Keras\" that\nremoves all of the complexity, leaving you an API containing only what\nyou need to know to efficiently develop and evaluate neural network\nmodels. This talk aims to present two use cases (facial recognition and\nsequence prediction) that uses Keras for model building and evaluation.\n",
  "duration": 1754,
  "language": "eng",
  "recorded": "2016-11-06",
  "speakers": [
    "Shubhabrata Roy"
  ],
  "thumbnail_url": "https://i.ytimg.com/vi/NUVdyeV0rkw/hqdefault.jpg",
  "title": "Deep learning with Keras",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=NUVdyeV0rkw"
    }
  ]
}