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Duration 21 hours
Course Outline
- Distribution in the Big Data Era
- Data mining methods (training on single-machine models + distributed prediction: traditional machine learning algorithms + MapReduce distributed prediction)
- Apache Spark MLlib
- Recommendations and Targeted Advertising:
- Aspects of Natural Language Processing
- Text clustering, text classification (labelling), synonyms
- User profile reconstruction, tagging system
- Strategies for recommendation algorithms
- Inter-class lift, intra-class lift, and precision
- Building the closed loop for recommendation algorithms
- Logistic Regression, RankingSVM
- Feature Extraction: (Deep learning and automatic feature extraction for graphics)
- Natural Language Processing
- 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 attending this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
