Course: Fundamentals of Machine Learning for Predictive Data Analytics
Instructors: Dr. Brian Mac Namee and Dr. John Kelleher
Where: Dublin, Ireland
When: 21-23 March, 2017
Cost: € 1,650
Predictive analytics applications use machine learning to build predictive models for applications including price prediction, risk assessment, and predicting customer behaviour. Based on the trainers' book,
"Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies" this course presents a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
" The course provided our company with an excellent introduction to the key concepts behind machine learning. Simple explanations of the core concepts and algorithms were provided along with practical worked examples. The course was engaging and interesting and delivered by experienced presenters who brought a wide range of practical experience and insights. I would recommend this course to anybody looking to apply machine learning algorithms in their work"
Jason Payne - Wood Group Kenny
" In three days John and Brian managed to impart a ton of technical knowledge in a relaxed, interactive manner. They also delivered a comprehensive methodology that allowed me to start right away on data analysis projects based on machine learning. The excellent facilities and course structure were a bonus"
Joe Fenech Conti - Loqus
Benefits of this Course
- Guides delegates through the most important topics in machine learning, and how they should be applied to build real-world relevant predictive analytics models
- Expert, instructor led tuition delivered in small groups
- Presents sophisticated machine learning theories, and how they are best applied in a business environment
- All delegates receive a copy of the book "Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies"
The course will cover the following key topics:
- What is predictive data analytics and what is it used for?
- What is machine learning?
- Developing predictive data analytics solutions for business problems
- Training machine learning models - inductive bias, generalisation, overfitting and underfitting
- Fundamentals of data analysis and data visualisation
- Deep dive on four key approaches to machine learning: Information-based, Error-based, Probability-based, and Similarity-based
- Evaluating predictive models