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Course Outline
- Distributed Systems for Big Data
- Data Mining Methods (Training Single Node + Distributed Predictions: Traditional Machine Learning Algorithms + MapReduce Distributed Predictions,)
- Apache Spark MLlib
- Recommendations and Precision Advertising:
- Components of Natural Language
- Text Clustering, Text Classification (Labeling), and Synonyms
- User Profile Reconstruction and Tagging Systems
- Strategies for Recommendation Algorithms
- Lift Between Classes, Lift Within Classes, and Precision Optimization
- Building a Closed Loop for Recommendation Algorithms
- Logistic Regression, Ranking SVM,
- Feature Recognition: (Automatic Feature Recognition for Deep Learning and Shapes)
- 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 (TSTM) Architecture
Requirements
There are no specific prerequisites required to join this course.
21 Hours
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
