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Duration 21 hours
Course Outline
- Distributed Systems for Big Data
- Data Mining Methods (Training Standalone 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, Label Systems
- Strategies for Recommendation Algorithms
- Inter-class Lift, Intra-class Lift, and Precision Metrics
- Building a Closed-Loop for Recommendation Algorithms
- Logistic Regression, Ranking SVM
- Feature Extraction: (Automatic Feature Extraction with Deep Learning and Graphs)
- Natural Language Processing
- 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 prerequisites for joining this course.
Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
