Staff writer Sun says she uses anaconda to install all packages on her windows gaming computer, so that she can easily use the GPU to train her neural networks. She’s a Mac user and want to spend minimal time configuring and setting up a development environment on windows. It just works. All her Jupyter Notebooks run, and it was easy to use CUDA to train her models on GPU.
Installation and Uninstall
~/is the home path on Mac. You need to locate where your miniconda is installed on your computer first.
$ rm -r ~/miniconda
command+Mto open the matrix helper to quickly enter matrix data.
$ conda list
$ conda install -c conda-forge opencv
$ conda env list
create -ncreates a new environment. We also specified the version of python we want to use
python=3. We also added the package we want to install as a suffix.
$ conda create -n my_env numpy
$ conda activate my_env
$ conda install pytorch torchvision -c pytorch
Advanced Use of Anaconda
.yamlto manage configuration and requirement files similar to modern Ruby on Rails and Node.js, front end development best practice.
$ conda env export > environment.yaml $ conda env create -f environment.yaml
$ conda remove package_name_1 package_name_2 $ conda remove scipy curl
conda update jupyterUpdate the kernel to the latest version of Python
conda install python=3Make Jupyter Notebook aware of new anaconda environment
ipython kernel install --name my_env_name --user. So the kernel can be set.
- Attend anaconda con conference