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Machine Learning and Deep Learning with Real Case Examples

Title Machine Learning and Deep Learning with Real Case Examples
Course code CM546-04-2018-C

Machine learning is a branch of Artificial Intelligence. In recent years, the concept of big data is highly sought after. The essence is to extract valuable information from massive data through various analysis techniques, provide data basis for various kinds of decision-making, Have data to predict the future. The course introduces the fundamentals and principles of machine learning, the associated algorithms and core technologies that enable students to use algorithms to analyze data.

  • Introduction
  • Linear Regression
  • Linear Algebra Review
  • Linear Regression with Multiple Variables
  • Logistic Regression
  • Regularization
  • Neural Network Representation
  • Neural Network Learning
  • Advice for Applying Machine Learning
  • Machine Learning System Design
  • Support Vector Machine (SVM)
  • Clustering
  • Dimensionality Reduction
  • Anomaly Detection
  • Recommender Systems
  • Large Scale Machine Learning
  • Application Example
  • Brief Introduction to Deep Learning
  • Quiz
Assessment In-class performance, assignments and test
Target audience
  • IT Technician
  • Software Developer / Designer
  • Any one who are interested in machine learning technologies
  • Know one of any programming language (ie know what is software programming)
  • High school math and statistical knowledge
  • Can read English materials
  • Students shall bring theire own laptop for class.
Class size 12
Instructor CPTTM Appointed Instructor(s)
Handout All training material provided by CPTTM
Instruction language Cantonese (supplemented with English)
Handout language English
Duration 40 hours in 16 sessions
Schedule 19:00-21:30, from Apr 17, 2018 to Jun 14, 2018 every Tuesday, Thursday, excluding May 1, 2018(Tuesday), May 22, 2018(Tuesday).
Fee MOP4,800
Venue Cyber-Lab (Rua Comandante Mata Oliveira, Ed. Associacao Industrial, 3-andar Macau)
Certificate Certificate of Completion/Merit issued by CPTTM (with at least 80% attendance and passed the assessment).
PDAC code ---

Course will use R and Octave as tools, student shall be able to install these tools by self.
Know how to install numpy, keras, tensorflow and other modules using python are recommended.

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