|23 Jul - 25 July 2018||9:00am - 6:00pm|
|Malaysia Room (2nd Floor, MaGIC) View map|
|Admission RM1800 (before promotional price)|
All our ticket for Artificial Intelligence Application (July) is now sold out.
You may find the next Artificial Intelligence Application in September.
This course will introduce the learner to applied machine learning and neural network with Python, focusing more on the techniques and methods than on the statistics behind these methods.
The course will start with a discussion of how machine learning is different than descriptive statistics, and the introduction to the scikit learn toolkit.
Lesson 1: Introduction to Machine Learning
Lesson 2: Supervised and unsupervised learning
Lesson 3: Cross Validation and Model Evaluation and Selection
Lesson 4: Introduction to Ensemble Models
Lesson 5: Introduction to Neural Network and Artificial Intelligence
Lesson 6: Machine Learning and Artificial Intelligence use cases
Register today to secure your seats!
If you have any enquiry about the course, please email us at email@example.com
Please be informed that we will get back to you within 3 working days.
Backed with 15 years of academic and research background, Dr Poo is a passionate practitioner in the area of Data Science, Machine Learning and Artificial Intelligence. A graduate of Nagoya Institute of Technology (Japan), Dr. Poo holds a Doctorate degree (Ph.D.) in Computer Science, a Master of Information Technology (UKM), and a Bachelor of Science (UKM). Dr. Poo applies his combination of research and industrial experience in big data analytics, data mining, Machine Learning and Artificial Intelligence to provide consultancy on data strategy for companies in various sectors including finance. telecommunication and technology startups.
Dr. John See Su Yang is currently working as senior lecturer at the Faculty of Computing and Informatics, Multimedia University (Cyberjaya campus) Malaysia. He is leading the Pattern Recognition and Analysis subgroup of the Center for Visual Computing, which resides at the Visual Processing (ViPr) Lab. His research interests are in computer vision and machine learning, particularly with the goal of finding effective and efficient algorithms for visual recognition tasks. Besides that he has delved into unconstrained face recognition in his Ph.D work, he have now moved on to other new areas such as long-term video surveillance, facial micro-expression recognition, image aesthetic evaluation and other research areas. Dr. John is one of the co-organizer of the TensorFlow and Deep Learning User Group Malaysia.