Bigdata and Deep Learning Lecture points(1)

Li Deng from Microsoft Research,gaven the lecture at Peking University at July 11-12,2015.
Link:普适计算与大数据

Basics

  1. What is Deep Learning
    https://en.wikipedia.org/wiki/Deep_learning

    Deep learninlg is a branch of Machine Learning based on a set of** algorithms** that attempt to model high-level abstractions in data by using model architectures,wich complex structures or otherwise,composed of multiple non-linear transformations.

  2. Review of Deep Learning Basics

    • Deep Learning(aka Deep Structured Learning,Hierarchical Learning)
    • Deep belief nets(DBN)
    • Boltzman machine(BM)
    • Restricted Boltzman machine(RBM)
    • Deep neural nets(DNN)
    • Deep auto-coder
    • Distributed representation
  3. Distributed Representation
    A representation of the observed data in such a way that they are modeled as being generated by the interactions of many hidden factors. A particular factor learned from configurations of other factors can often generalize well. Distributed representations form the basis of deep learning.

  4. More on “Deep Learning”
    Four Definition

    • Definition1:
      A class of machine learning techniques that exploit many layers of non-linear information processing for supervised or unsupervised feature extraction and transformation,and for pattern analysis and classification.
    • Definition2:
      A sub-field within machine learning that is based on algorithms for learning multiple levels o representation in order to model complex relation ships among data.
    • Definition3:
      A sub-field of machine learning that is based on learning several levels of representations,corresponding to a hierarchy of features or factors or concepts,where higher-level concepts are defined from lower-level ones,and the same lower-level concepts can help to define many higher-level concepts.
      See http://en.wikipedia.org/wiki/Deep_learning.

    • Definition4:
      Deep Learning is about learning multiple levels of representation and abstraction that help to make sense of data such as images,sound,and text.
      See https://github.com/lisa-lab/DeepLearningTutorials


Highlight of Deep Learning in the Era of Big Data

Deep Learing vs.Machince Learning

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Recipe for(Supervised) Machine Learning with Big Data

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Impact of Deep learning in Speech technology

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