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.