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Duration 21 hours
Course Outline
- Distributed Systems in Big Data
- Data Mining Methods (Training Single Models + Distributed Predictions: Traditional Machine Learning Algorithms + MapReduce Distributed Predictions)
- Apache Spark MLlib
- Recommendations and Targeted Advertising:
- Components of Natural Language
- Text Clustering, Text Classification (Tagging), and Synonyms
- User Profile Reconstruction and Tagging Systems
- Strategies for Recommendation Algorithms
- Inter-class Lift, Intra-class Lift, and Precision
- Building a Closed Loop for Recommendation Algorithms
- Logistic Regression, RankingSVM
- Feature Identification: (Automatic Feature Extraction for Deep Learning and Graphs)
- Natural Language
- Chinese Word Segmentation
- Topic Models (Text Clustering)
- Text Classification
- Keyword Extraction
- Semantic Analysis, Semantic Parser, and Word2Vec to Word Vectors
- RNN Long Short-Term Memory (LSTM) Architecture
Requirements
There are no specific prerequisites for enrolling in this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
