- 16 — 17 Apr 2024
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Time9:00 until 14:00
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LocationTU/e Campus, Eindhoven (Luna 1.050 on the 16th of April, Neuron 0.262 on the 17th of April)
What?
On day 1 of this course you will:
- Understand the fundamental theories of machine learning and the intuitions/ideas behind the algorithms
- Work with a high-level machine learning API (Keras)
- Explore hyperparameter space to improve a neural network
- Understand the pitfalls of classic machine learning algorithms
On day 2 of this course you will learn:
- How to set up your software environment
- About the technical capabilities of modern day CPUs and GPUs
- How to identify bottlenecks in your code
Who?
Everyone interested in getting familiar with machine learning at scale, from the beginning up to more advanced topics
Prerequisites
- Basic knowledge on statistics
- Basic knowledge on linear algebra
- Basic knowledge on Python programming. Some experience with the use of Jupyter Notebooks is desirable, but not essential.
* Basic knowledge on parallel computing is helpful, but not required.