UCL Module | CS | UCL Moodle Page
Term 1 (Autumn), Academic Year 2021-22
Module Lead
Yipeng Hu yipeng.hu@ucl.ac.uk
| Tutors & TAs | |
|---|---|
| Dr Andre Altmann | a.altmann@ucl.ac.uk |
| Dr Ziyi Shen | --- |
| Ahmed Shahin | ahmed.shahin.19@ucl.ac.uk |
| Shaheer Saeed | shaheer.saeed.17@ucl.ac.uk |
| Kate Yiwen Li | yiwen.li@st-annes.ox.ac.uk |
| Sophie Martin | s.martin.20@ucl.ac.uk |
| Liam Chalcroft | liam.chalcroft.20@ucl.ac.uk |
| Mark Pinnock | mark.pinnock.18@ucl.ac.uk |
| Iani Gayo | iani.gayo.20@ucl.ac.uk |
| Qi Li | qi.li.21@ucl.ac.uk |
The module tutorials (see bellow) and coursework use Python, NumPy and an option between TensorFlow and PyTorch. The Development environment document contains details of the supported development environment, though it is not mandatory.
To run the tutorial examples, follow the instruction below.
First, set up the environment:
conda create --name comp0090 tensorflow pytorch torchvision
conda activate comp0090Additional libraries required for individual tutorials are specified in the readme file in each tutorial directory.
Scripts with "_tf" and "_pt" postfix are using TensorFlow 2 and PyTorch, respectively.
All visual examples will be saved in files, without requiring graphics.
Then, change directory cd to each individual tutorial folder and run individual training scripts, e.g.:
python train_pt.py or
python train_tf.py Image classification
Image segmentation
A collection of books and research papers is provided in the Reading List.