Machine Learning

  1. Objectives
  2. Contents
    1. NVIDIA Deep Learning GPU Training System, DIGITS. https://developer.nvidia.com/digits
      1. https://www.leiphone.com/news/201706/k7eKW8nLuKtZA2NG.html
    2. 10 Must visit MOOC for Machine Learning (开发者入门必读:最值得看的十大机器学习公开课). https://www.leiphone.com/news/201701/0milWCyQO4ZbBvuW.html?ulu-rcmd=1_5021df_hot_0_28b56ea43ea2400e92d359d72e416b97
    3. 未来 3-5 年内,哪个方向的机器学习人才最紧缺?https://www.leiphone.com/news/201709/cSLFrWjxq2YIcEom.html
  3. Future Trends
    1. Foundations
      1. Regression
      2. Classification
      3. Neural Networks
      4. Data compression and visualization
      5. Unsupervised and semi-supervised learning
    2. Hottest in 2016-17
      1. GAN
      2. multi-table learning
      3. transfer learning
  4. References
    1. 「Deep Learning」读书系列分享. https://www.leiphone.com/news/201708/LEBNjZzvm0Q3Ipp0.html
    2. Download book “Deep Learning” in pdf. https://pan.baidu.com/s/1pLshf2z#list/path=%2F%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD
    3. AI threats to professions: http://businessfocus.presslogic.com/2017/08/18/article/32725/
    4. Intel Nervana Academy. https://software.intel.com/en-us/ai-academy/training?https%3A%2F%2Fad_doubleclick_net%2Fddm%2Fclk%2F403024834%3B203250248%3Bp=
    5. An Introduction to Statistical Learning with Applications in R. http://www-bcf.usc.edu/~gareth/ISL/
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Machine Learning

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