Course Outline

  1. Distribution big data
    1. Data mining methods (training single systems + distributed prediction: traditional machine learning algorithms + Mapreduce distributed prediction)
    2. Apache Spark MLlib
  2. Recommendations and Advertising:
    1. Natural language
    2. Text clustering, text categorization (labeling), synonyms
    3. User profile restore, labeling system
    4. Recommended algorithms
    5. Insuring the accuracy of "lift" between and within categories
    6. How to create closed loops for recommendation algorithms
  3. Logical regression, RankingSVM,
  4. Feature recognition (deep learning and automatic feature recognition for graphics)
  5. Natural language
    1. Chinese word segmentation
    2. Theme model (text clustering)
    3. Text classification
    4. Extract keywords
    5. Semantic analysis, semantic parser, word2vec (vector to word)
    6. RNN long-term memory (TSTM) architecture
  21 Hours
 

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Testimonials

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn

This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.

This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.

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