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Who should attend
- IT professionals who need to apply pattern recognition and machine learning techniques to develop intelligent systems.
- IT professionals who need to assess and compare pattern recognition and machine learning techniques.
- Domain specialists and anyone planning to undertake pattern recognition and machine learning projects.
About the course
Machine learning uses statistical techniques to give computers the ability to "learn" with data without being explicitly programmed. With the most recent breakthrough in the area of deep learning, machine learning has made a big leap. Deep learning has enabled many practical applications in the areas of computer vision, natural language processing, etc.
There are many machine learning techniques available to develop intelligent systems and solve real-world complex problems. In this new era of AI and machine learning, it is important for IT professionals especially AI engineers to acquire the cutting-edge knowledge and skills in this area.
This course will be useful for IT and AI professionals to acquire advanced pattern recognition and machine learning techniques, especially deep learning techniques. Participants will learn how to select and apply the most suitable machine learning techniques to solve the given problems and develop intelligent systems. This course covers general principles and techniques with a unique focus on practical applications.
At the end of the course, participants will be able to:
- Assess and compare the suitability of advanced pattern recognition and machine learning techniques across a range of problem domains
- Apply deep learning and other advanced machine learning techniques to solve given problems
- Build intelligent systems using deep learning and other advanced pattern recognition techniques
- Analyse the results and suggest possible improvements
What Will Be Covered
- Intro to Pattern Recognition and Machine Learning Systems
- Neural Network Basics
- Neural Network Modeling and Design
- Deep Learning Systems
- Convolutional Neural Networks
- Recurrent Neural Networks
- Hybrid and Ensemble Approaches
- Practical case studies and workshops
Dr. Zhu Fangming is with the Institute of Systems Science of the National University of Singapore (NUS-ISS). He currently lectures in the Master of Technology programme in the areas of evolutionary computation, neural networks and data mining. Prior to joining ISS, he was a postdoctoral fellow i...
Jen Hong develops algorithms. He specializes in deep learning, image processing and medical image diagnosis. He designs illustrations, web page and posters. He plays piano. He invented a mathematical model to analyze dry eye. He used deep learning to correct medical images. He trained deep learni...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
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