This online course “Introduction to Deep Learning” will teach you the theoretical ánd practical basics of deep learning. In the course, you’ll learn how deep neural networks work and how they are optimized.
Introduction to Deep Learning
Regularity
Every 2 months
Trainers
Caspar van Leeuwen
Monica Rotulo
What will you learn?
During our hands-on sessions you will have the opportunity to work on our high-performance systems and train neural networks to solve an image classification problem. We’ll cover various neural network architectures: from a basic fully connected network, to a convolutional neural network and variational auto-encoders (time permitting).
In this course you will learn to:
- Understand how a neuron and neural network works
- Understand how a neural network is trained
- Explore the effect of hyperparameters on neural network performance
- Work with a high-level machine learning API (Keras)
For Whom?
Everyone interested in deep learning, but with no (or little) current experience & knowledge.
Prerequisites
- Python
- Basics of linear algebra
- Basic statistics
Topics
- Neural network: basics
- How does a neuron work?
- Fully connected networks
- Training/optimizing a neural network
- Convolutional neural networks (CNNs)
- (Variational) Auto-Encoders
Costs
Participation is free of charge
The language of instruction is English
Do you want to participate?
In our agenda you can see all the upcomping trainings and events