Fast.ai is a popular deep learning library that provides high-level APIs for training and deploying deep learning models with ease. In this article, we will discuss how to install the fast.ai module and set up the necessary dependencies to get started with deep learning using the fastai library.
Step 1: Install Anaconda or Miniconda
The first step in installing fast.ai is to have Anaconda or Miniconda installed on your system. Anaconda is a package manager, an environment manager, and a collection of over 7,500 open-source packages, while Miniconda is a minimal installer for conda. You can download and install Anaconda or Miniconda from their respective websites.
Step 2: Create a Conda Environment
Once Anaconda or Miniconda is installed, open a terminal and create a new conda environment for fast.ai using the following command:
“`conda create -n fastai python=3.7“`
This will create a new conda environment named fastai with Python version 3.7.
Step 3: Activate the Conda Environment
After creating the conda environment, activate it using the following command:
“`conda activate fastai“`
Step 4: Install PyTorch
Fast.ai is built on top of PyTorch, so you’ll need to install PyTorch as a prerequisite. Install PyTorch using the following conda command:
“`conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch“`
This command will install PyTorch, torchvision, and torchaudio with the specified cuda toolkit version.
Step 5: Install fastai
Now that PyTorch is installed, you can install the fastai module using the following command:
“`conda install -c fastai fastai“`
This will install the latest version of the fastai library in the fastai conda environment.
Step 6: Set Up Jupyter Notebook
To start using fast.ai in a Jupyter notebook, install Jupyter notebook in the fastai conda environment using the following command:
“`conda install jupyter“`
Once Jupyter is installed, you can launch a Jupyter notebook from the activated fastai environment:
“`jupyter notebook“`
This will open a new notebook in your default web browser where you can start using fastai to build and train deep learning models.
In conclusion, the fastai library is a powerful tool for deep learning that can be installed with just a few simple steps. By following the instructions outlined in this article, you can quickly set up the necessary environment and start using fastai to work on your deep learning projects. With its high-level APIs and easy-to-use interface, fastai is a great choice for both beginners and experienced deep learning practitioners.
