Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
- Distributed Systems under Big Data
- Data Mining Methods (Training single models + 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 (labeling), Synonyms
- User profile reconstruction, Tag systems
- Strategies for recommendation algorithms
- Lift between classes, Lift within classes, How to achieve precision
- How to build a closed loop for recommendation algorithms
- Logistic Regression, RankingSVM,
- Feature Identification: (Deep learning and automatic feature identification for graphics)
- Natural Language
- Chinese word segmentation
- Topic modeling (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 join this course.
21 Hours
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
