深度學習閱讀清單

jopen 9年前發布 | 29K 次閱讀 深度學習 機器學習

包括:免費電子書、課程、視頻、講義、論文、站點、框架等等

Deep learning Reading List

Following is a growing list of some of the materials i found on the web for Deep Learning beginners.

Free Online Books

  1. Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville
  2. Neural Networks and Deep Learning by Michael Nielsen
  3. Deep Learning by Microsoft Research
  4. Deep Learning Tutorial by LISA lab, University of Montreal
  5. </ol>

    Courses

    1. Machine Learning by Andrew Ng in Coursera
    2. Neural Networks for Machine Learning by Geoffrey Hinton in Coursera
    3. Neural networks class by Hugo Larochelle from Université de Sherbrooke
    4. Deep Learning Course by CILVR lab @ NYU
    5. </ol>

      Video and Lectures

      1. How To Create A Mind By Ray Kurzweil - Is a inspiring talk
      2. Deep Learning, Self-Taught Learning and Unsupervised Feature Learning By Andrew Ng
      3. Recent Developments in Deep Learning By Geoff Hinton
      4. The Unreasonable Effectiveness of Deep Learning by Yann LeCun
      5. Deep Learning of Representations by Yoshua bengio
      6. Principles of Hierarchical Temporal Memory by Jeff Hawkins
      7. Machine Learning Discussion Group - Deep Learning w/ Stanford AI Lab by Adam Coates
      8. Making Sense of the World with Deep Learning By Adam Coates
      9. Demystifying Unsupervised Feature Learning By Adam Coates
      10. Visual Perception with Deep Learning By Yann LeCun
      11. </ol>

        Papers

        1. ImageNet Classification with Deep Convolutional Neural Networks
        2. Using Very Deep Autoencoders for Content Based Image Retrieval
        3. Learning Deep Architectures for AI
        4. CMU’s list of papers
        5. </ol>

          Tutorials

          1. UFLDL Tutorial 1
          2. UFLDL Tutorial 2
          3. Deep Learning for NLP (without Magic)
          4. A Deep Learning Tutorial: From Perceptrons to Deep Networks
          5. </ol>

            WebSites

            1. deeplearning.net
            2. deeplearning.stanford.edu
            3. </ol>

              Datasets

              1. MNIST Handwritten digits
              2. Google House Numbers from street view
              3. CIFAR-10 and CIFAR-100
              4. IMAGENET
              5. Tiny Images 80 Million tiny images
              6. Flickr Data 100 Million Yahoo dataset
              7. Berkeley Segmentation Dataset 500
              8. </ol>

                Frameworks

                1. Caffe
                2. Torch7
                3. Theano
                4. cuda-convnet
                5. Ccv
                6. NuPIC
                7. DeepLearning4J
                8. </ol>

                  Miscellaneous

                  1. Google Plus - Deep Learning Community
                  2. Caffe Webinar
                  3. 100 Best Github Resources in Github for DL
                  4. Word2Vec
                  5. Caffe DockerFile
                  6. TorontoDeepLEarning convnet
                  7. Vision data sets
                  8. Fantastic Torch Tutorial My personal favourite. Also check out gfx.js
                  9. Torch7 Cheat sheet
                  10. </ol> </div> </div> </div> http://jmozah.github.io/links/

 本文由用戶 jopen 自行上傳分享,僅供網友學習交流。所有權歸原作者,若您的權利被侵害,請聯系管理員。
 轉載本站原創文章,請注明出處,并保留原始鏈接、圖片水印。
 本站是一個以用戶分享為主的開源技術平臺,歡迎各類分享!