Configure Your Mac for PyTorch Machine Learning in Just 11 Minutes – Compatible with M1 and M2 Models

Setting up your Mac for Machine Learning with PyTorch is essential for anyone looking to work with deep learning models on their computer. Whether you have a new M1 or M2 Mac, the process is generally the same and can be done in just 11 minutes. In this tutorial, we will walk you through the steps to set up your Mac for Machine Learning with PyTorch.

Step 1: Install Homebrew
Homebrew is a package manager for macOS that allows you to easily install and manage software packages on your Mac. To install Homebrew, open Terminal and paste the following command:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Follow the on-screen instructions to complete the installation.

Step 2: Install Python
PyTorch requires Python as its programming language, so the next step is to install Python on your Mac. Homebrew makes this process simple with the following command:
brew install python

Step 3: Install PyTorch
Now that Python is installed, you can use pip, the Python package manager, to install PyTorch. Run the following command in Terminal:
pip install torch torchvision torchaudio

Step 4: Install Jupyter Notebook
Jupyter Notebook is a popular tool among data scientists and machine learning engineers for creating and sharing documents that contain live code, equations, visualizations, and narrative text. You can install Jupyter Notebook with the following command:
pip install jupyter

Step 5: Install Matplotlib
Matplotlib is a data visualization library in Python that creates static, animated, and interactive visualizations in Python. To install Matplotlib, enter the following command:
pip install matplotlib

Step 6: Install Pandas
Pandas is a powerful data manipulation library in Python that provides data structures and data analysis tools for working with structured data. To install Pandas, run the following command:
pip install pandas

Step 7: Install Scikit-learn
Scikit-learn is a machine learning library in Python that provides simple and efficient tools for data mining and data analysis. To install Scikit-learn, use the following command:
pip install scikit-learn

Step 8: Test Your Installation
To test that PyTorch and all the necessary libraries have been installed correctly, open a new terminal window and start a Jupyter Notebook by typing:
jupyter notebook

Create a new Python notebook and enter the following code:

import torch
print(torch.__version__)
import torchvision
print(torchvision.__version__)
import torchaudio
print(torchaudio.__version__)
import matplotlib
print(matplotlib.__version__)
import pandas
print(pandas.__version__)
import sklearn
print(sklearn.__version__)

Run the code cell, and if you see the versions of all the libraries printed without any errors, then congratulations, you have successfully set up your Mac for Machine Learning with PyTorch!

In just 11 minutes, you have installed and configured all the necessary tools and libraries to start working on machine learning projects with PyTorch on your Mac. Happy coding!