{
  "id": 35935,
  "title": "Where can i use deep learning and where only deep learning will help ?",
  "url": "/competitions/passenger-screening-algorithm-challenge/discussion/35935",
  "author_name": "",
  "post_date": "2017-07-07T12:00:16.068220300Z",
  "votes": -10,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Please explain with some real time situation.</p>",
  "messages": [
    {
      "id": "200275",
      "postDate": "07/07/2017 12:00:16",
      "content": "<p>Please explain with some real time situation.</p>",
      "rawMarkdown": "Please explain with some real time situation.",
      "votes": null
    },
    {
      "id": "204148",
      "postDate": "07/17/2017 17:54:41",
      "content": "<p>hey BhuvaneshwaranK,</p>\n\n<p>Deep Learning can be used in variety of use cases. Images, Video, Text, Time-Series, Sound are some use-cases where Deep Learning really shines. The exclusivity of Deep Learning is in modeling problems where for example you are building layers of abstraction to model the data. Convolutional Neural Network (CNN) is a great example of such technique which can be applied on Images, Audio and Video. DLs can also be exclusively used where you have huge amounts of data and have created a very deep layered NN to model the data. I would recommend this blog <a href=\"http://colah.github.io/\">http://colah.github.io/</a> to start with for further reading and also Google Cloud ML Engine Getting Started page where you will find some well curated resources <a href=\"https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction\">https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction</a>. Please feel free to respond back if you have additional questions. </p>\n\n<p>Puneith</p>",
      "rawMarkdown": "hey BhuvaneshwaranK,\n\nDeep Learning can be used in variety of use cases. Images, Video, Text, Time-Series, Sound are some use-cases where Deep Learning really shines. The exclusivity of Deep Learning is in modeling problems where for example you are building layers of abstraction to model the data. Convolutional Neural Network (CNN) is a great example of such technique which can be applied on Images, Audio and Video. DLs can also be exclusively used where you have huge amounts of data and have created a very deep layered NN to model the data. I would recommend this blog http://colah.github.io/ to start with for further reading and also Google Cloud ML Engine Getting Started page where you will find some well curated resources https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction. Please feel free to respond back if you have additional questions. \n\nPuneith",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 204148,
      "author_name": "puneith",
      "author_url": "",
      "post_date": "07/17/2017 17:54:41",
      "content": "<p>hey BhuvaneshwaranK,</p>\n\n<p>Deep Learning can be used in variety of use cases. Images, Video, Text, Time-Series, Sound are some use-cases where Deep Learning really shines. The exclusivity of Deep Learning is in modeling problems where for example you are building layers of abstraction to model the data. Convolutional Neural Network (CNN) is a great example of such technique which can be applied on Images, Audio and Video. DLs can also be exclusively used where you have huge amounts of data and have created a very deep layered NN to model the data. I would recommend this blog <a href=\"http://colah.github.io/\">http://colah.github.io/</a> to start with for further reading and also Google Cloud ML Engine Getting Started page where you will find some well curated resources <a href=\"https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction\">https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction</a>. Please feel free to respond back if you have additional questions. </p>\n\n<p>Puneith</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "200275": "Please explain with some real time situation.",
    "204148": "hey BhuvaneshwaranK,\n\nDeep Learning can be used in variety of use cases. Images, Video, Text, Time-Series, Sound are some use-cases where Deep Learning really shines. The exclusivity of Deep Learning is in modeling problems where for example you are building layers of abstraction to model the data. Convolutional Neural Network (CNN) is a great example of such technique which can be applied on Images, Audio and Video. DLs can also be exclusively used where you have huge amounts of data and have created a very deep layered NN to model the data. I would recommend this blog http://colah.github.io/ to start with for further reading and also Google Cloud ML Engine Getting Started page where you will find some well curated resources https://cloud.google.com/ml-engine/docs/how-tos/getting-started-training-prediction. Please feel free to respond back if you have additional questions. \n\nPuneith"
  },
  "source": "meta"
}