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Course Outline

  1. Distributed Systems in Big Data
    1. Data Mining Methods (Training Single-Model + Distributed Prediction: Traditional Machine Learning Algorithms + MapReduce Distributed Prediction)
    2. Apache Spark MLlib
  2. Recommendations and Precision Advertising:
    1. Natural Language Components
    2. Text Clustering, Text Classification (Labeling), Synonyms
    3. User Profile Reconstruction, Label System
    4. Strategies for Recommendation Algorithms
    5. Inter-class lift, Intra-class lift, and Precision Optimization
    6. Building a Closed-Loop for Recommendation Algorithms
  3. Logistic Regression, Ranking SVM
  4. Feature Recognition: (Automated Feature Recognition in Deep Learning and Graphs)
  5. Natural Language
    1. Chinese Word Segmentation
    2. Topic Models (Text Clustering)
    3. Text Classification
    4. Keyword Extraction
    5. Semantic Analysis: Semantic Parser, Word2Vec to Word Vectors
    6. RNN Long Short-Term Memory (LSTM) Architecture

Requirements

No specific prerequisites are required for this course.

 21 Hours

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Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3900 € + VAT*

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