Nat-D / teaching

code for teaching deep learning

Install Library

1. install conda

   • create conda environment conda create -n learn python=3.9
   • activate the conda environment conda activate learn

2. install pytorch (https://pytorch.org/get-started/locally/)

   without gpu:

   • conda install pytorch torchvision torchaudio cpuonly -c pytorch

   or with gpu:

   • conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch

3. install pandas

   • conda install pandas

4. install tensorboard

   • pip install tensorboard

5. (segmentation) install albumentation

   • conda install -c conda-forge imgaug
   • conda install -c conda-forge albumentations

6. (seq2seq) install spacy

   • pip install -U spacy
   • python -m spacy download en_core_web_sm
   • python -m spacy download de_core_news_sm

7. (seq2seq) install torchtext and torch-data

   • conda install -c pytorch torchtext torchdata

• conda install portalocker

Download Dataset

https://drive.google.com/drive/folders/1feL5X6epYQiGaT-dHpgV7yWU7_ZthVVI?usp=sharing

References

1. https://github.com/aladdinpersson/Machine-Learning-Collection
2. https://pytorch.org/tutorials/
3. https://www.kaggle.com/competitions/dogs-vs-cats
4. http://www.cvlibs.net/datasets/kitti/