Setting up Your M4 Mini for AI and ML - Part 1

Setting up your M4 Mini for AI and ML development with Miniconda, IDEs, JupyterLab and more.

Ndamulelo Nemakhavhani

1 April 2025 · 2 min read

Setting up Your M4 Mini for AI and ML - Part 1#

1. Installing Miniconda#

Download Miniconda for macOS (Apple Silicon) from the official website: https://docs.conda.io/en/latest/miniconda.html
Run the installer using the following command:
```
bash Miniconda3-latest-MacOSX-arm64.sh
```

Add Conda to PATH:

source ~/.zshrc  # If using zsh (default shell in macOS)

Verify the installation:
```
conda --version
```

2. Installing IDEs: VSCode / PyCharm Community#

VSCode:#

Download and install from https://code.visualstudio.com/
Install using Homebrew:
```
brew install --cask visual-studio-code
```

Download and Install VsCode Python extension:

# Alternatively, you can install the extension using the command line:
code --install-extension ms-python.python

PyCharm Community:#

Download and install from https://www.jetbrains.com/pycharm/download/

Cursor(Optional):#

Download and install from https://cursor.so/

3. Updating Git#

Check if Git is installed:
```
git --version
```
If not installed, install it via Homebrew:
```
brew install git
```

4. Creating an AI Environment with Conda#

Create a new conda environment:
```
conda create --name ai python=3.12
```
Activate the environment:
```
conda activate ai
```

5. Installing JupyterLab#

Install JupyterLab in the conda environment:
```
conda install -c conda-forge jupyterlab
```
Run JupyterLab:
```
jupyter lab
```

Example dataset for testing:

curl -o iris.csv https://raw.githubusercontent.com/jbrownlee/Datasets/master/iris.csv

Load the dataset in JupyterLab:

import pandas as pd
df = pd.read_csv('iris.csv', header=None)
df.head()

6. Installing Python Dependency Management Tools#

Poetry:#

Install Poetry:

curl -sSL https://install.python-poetry.org | python3 -

Configure Poetry:

poetry config virtualenvs.in-project true

UV:#

Install UV:

curl -LsSf https://astral.sh/uv/install.sh | sh

7. Running an Example Project - Build A Chatbot using Github Models#

Visit Github Models to pick a free AI model for your project.
Create a Personal Access Token to use with the Github Models
Run Github Models Example
Bonus: Use Chainlit to create a web app to chat with your AI model:
```
poetry add chainlit
touch app.py
chainlit run app.py
```

Next Steps#

Explore more AI/ML libraries like TensorFlow, PyTorch, and Scikit-Learn.
Set up Docker and containerized environments for better reproducibility.