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Course Outline
- Distributed Systems in Big Data
- Data mining methods (training single models + distributed prediction: traditional machine learning algorithms + MapReduce distributed prediction)
- Apache Spark MLlib
- Recommendation and Precision Targeted Advertising:
- Natural Language Processing components
- Text clustering, text classification (labels), synonyms
- User profile recovery, label systems
- Strategies for recommendation algorithms
- Lift between classes, intra-class lift, and how to achieve precision
- How to build a closed loop for recommendation algorithms
- Logistic Regression, RankingSVM,
- Feature Recognition: (Deep Learning and Graph-based Automatic Feature Recognition)
- Natural Language
- Chinese word segmentation
- Topic Models (Text Clustering)
- Text Classification
- Keyword Extraction
- Semantic Analysis: semantic parser, Word2Vec to word vectors
- RNN Long Short-Term Memory (LSTM) Architecture
Requirements
There are no specific requirements to participate in this course.
21 Hours
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
