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Duration 21 hours
Course Outline
- Distributed Systems for Big Data
- Data Mining Techniques (Single-node training + Distributed prediction: Traditional Machine Learning algorithms + MapReduce distributed prediction)
- Apache Spark MLlib
- Recommendations and Precision Advertising:
- Components of Natural Language Processing
- Text clustering, text classification (labelling), synonyms
- User profile reconstruction, tag systems
- Strategies for recommendation algorithms
- Inter-class lift, intra-class lift, and achieving precision
- Building closed-loop feedback for recommendation algorithms
- Logistic Regression, RankingSVM
- Feature Recognition: (Automatic feature recognition in deep learning and graphics)
- 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 prerequisites for this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
