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Duration 21 hours
Course Outline
- Distributed Systems for Big Data
- Data Mining Techniques (Training Standalone + 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), and Synonyms
- User Profile Reconstruction and Tagging Systems
- Strategies for Recommendation Algorithms
- Between-class Lift, Within-class Lift, and Precision Optimization
- Building a Closed Loop for Recommendation Algorithms
- Logistic Regression and RankingSVM
- Feature Extraction: (Automated Feature Extraction for Deep Learning and Graphs)
- Natural Language Processing
- Chinese Word Segmentation
- Topic Models (Text Clustering)
- Text Classification
- Keyword Extraction
- Semantic Analysis: Semantic Parser and Word2Vec 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.
