The Hands-on Machine Learning course is developed by Attila Houtkooper and the Trifork Amsterdam Machine Learning team. The team are on the cutting-edge of machine learning techniques and have worked on an impressive variety of real-world projects over the last few years.
Now it's your turn to benefit from their wealth of knowledge and practical experience.
Delve into the detail on how to actually apply machine learning to your daily work as a developer, whilst having a confident grasp of the underlying theories.
Topics Overview for Day 1
- Introduction to Machine Learning
- Supervised learning
- Unsupervised learning
- Data preprocessing
- Under- & overfitting
- SciKit Learn / TensorFlow libraries in Python
Topics Overview for Day 2
- (Convolutional) Neural Networks
- Recurrent Neural Networks
- Transfer Learning
- GPU servers on AWS
- Practical use-cases
- A basic understanding of data science concepts and the Python language is expected
- About two weeks before the start of the course, you will receive a preparation pack that details what you should know
- Developers are expected to bring their own laptop
- Instructor-led course given by skilled staff
- Best practices and know-how embedded in hands-on labs
- Interactive learning environment with strong Q&A
- Course delivered in English at our training rooms at 9 Rijnsburgstraat, Amsterdam
About the Trainer:
Attila is a Principal Machine Learning Architect at Trifork Amsterdam. He has worked in fintech, transport, healthcare and publishing. He facilitates the delivery of the best possible software by his team, by finding the optimal software quality-to-features ratio and striving for good software engineering, whilst ensuring delivery of the business requirements. Attila is currently studying for his MBA at Erasmus University to bring business principles to the software engineering world.