Pattern Recognition and Machine Learning Systems
About This 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.
This course is part of the Artificial Intelligence and Graduate Certificate in Pattern Recognition Systems Series offered by NUS-ISS.
What You'll Learn
� 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
Entry Requirements
Please see course weblink for more information