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.
Duration 21 hours
Course Outline
- Distributed Systems under Big Data
- Data mining methods (training single-machine models + distributed prediction: traditional machine learning algorithms + MapReduce distributed prediction)
- Apache Spark MLlib
- Recommendations and Precision Ad Delivery:
- Components of natural language
- Text clustering, text classification (labeling), synonyms
- User profile reconstruction, tagging systems
- Strategies for recommendation algorithms
- Inter-class lift, intra-class lift, and how to achieve precision
- How to build a closed loop for recommendation algorithms
- Logistic Regression, RankingSVM,
- Feature Extraction: (Automatic feature extraction for deep learning and graph structures)
- Natural Language
- Chinese word segmentation
- Topic models (text clustering)
- Text classification
- Key phrase extraction
- Semantic analysis: semantic parsers, Word2Vec to word vectors
- RNN Long Short-Term Memory (LSTM) Architecture
Requirements
There are no specific requirements for participating in this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
