This lesson is still being designed and assembled (Pre-Alpha version)

Learn Deep learning with Python

You will learn how to program a neural network with hidden layers (deep-learning) and the necessary theory behind.

You will learn how to apply convolutional neural networks in image-classification problems on the example of geospatial images.

Prerequisites

Laptop with Anaconda-navigator installed, python3; knowledge of python in Carpentry course level. See setup instructions to prepare your laptop for the workshop

Schedule

Setup Download files required for the lesson
00:00 1. Introduction What is deep learning?
What is a computational graph?
What is a neural network?
How to start deep learning with Python?
00:00 2. PyTorch basics Which framework choosing for deep learning?
What is PyTorch?
00:00 3. Regression with PyTorch How using PyTorch for multi-layered neural network?
Which neural network for regression?
00:00 4. Artificial Neural Network (ANN) How to prepare data?
How to load data?
How to run your ANN with your data?
00:00 5. Convolutional Neural Network (CNN) How to prepare data?
How to load data?
How to run your classifier with your data?
00:00 6. Recurrent Neural Network (RNN) How to prepare data?
How to load data?
How to run your classifier with your data?
00:00 7. Data Parallelism with Pytorch
00:00 8. After the workshop What is the UiO studyGroup?
What can I expect from the StudyGroup?
00:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.