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Duration 21 hours
Course Outline
- Distributed Systems for Big Data
- Data mining techniques (training single-node models + distributed predictions: traditional machine learning algorithms + MapReduce distributed prediction)
- Apache Spark MLlib
- Recommendations and Precision Advertising:
- Components of Natural Language
- Text clustering, text classification (labelling), synonyms
- User profile reconstruction and tagging systems
- Strategies for recommendation algorithms
- Lift between classes, lift within classes, and achieving precision
- Building a closed-loop system for recommendation algorithms
- Logistic Regression, RankingSVM
- Feature Extraction: (Automated feature extraction via deep learning and graphical models)
- Natural Language
- Chinese word segmentation
- Topic models (text clustering)
- Text classification
- Keyword extraction
- Semantic analysis: semantic parsers, word2vec to word vectors
- RNN Long Short-Term Memory (LSTM) Architecture
Requirements
There are no specific requirements to participate in this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
