BI-AI_hands_on

💳 Credit

basic python grammer and cnn introduction

PUll from this tutorial

introducing neural prior into CNN and evaluating similarity

This was heavily borrowed and adapted from this tutorial (Based on Brain-Score)

✍️ How to Use

Have you used command line/terminal and Anaconda before?

No Experience

Simply click on the following link to open a mybinder application by clicking the button below:

Note: This may take several minutes to open.

Some Experience

This is recommended since mybinder has limited resources. These instructions were tested for a Windows machine.

1. Install Anaconda by following the prompts in the link, just keep clicking next (it may warn you that you have a space in your directory, this should be fine).
2. Clone this repo to your local directory (git clone or download .zip).
3. Open Anaconda Prompt (anaconda3) from the start menu and move to where you cloned this repo (for me I had to cd Documents\cnn-pytorch-tutorial-main\cnn-pytorch-tutorial-main).
4. Create a new virtual conda environment with: conda create -n cnn-tutorial
5. Activate this new environment by running: conda activate cnn-tutorial. You should now see the following in your terminal:

(cnn-tutorial) C:>

6. Install ipykernel by running: conda install ipykernel.
7. Create a Jupyter Kernel and link to your environment by running: python -m ipykernel install --user --name=cnn-tutorial.
8. Install key pacakges:
   • update env conda env update --file binder/environment.yml
9. Deactivate the conda environment by running conda deactivate. (We should still be in the directory with folders such as notebook and binder with the same structure as this repo).
10. Start Jupyter Lab by running jupyter lab and make sure the kernel set is cnn-tutorial.