Master NumPy for AI/ML: arrays, linear algebra, broadcasting, and data manipulation with Jupyter notebooks.
This repository provides practical, hands-on NumPy tutorials specifically designed for AI and machine learning practitioners. Maintained by HERE AND NOW AI, each notebook focuses on the NumPy concepts most relevant to building and understanding AI/ML models.
From the basics of array creation and manipulation to advanced techniques like broadcasting, vectorization, and linear algebra operations, this series builds your NumPy intuition from the ground up. All examples use real data scenarios common in AI workflows.
Whether you are just starting out with Python for AI or want to sharpen your numerical computing skills, these notebooks give you the foundation to work confidently with frameworks like NumPy, TensorFlow, and PyTorch.
- Interactive Jupyter notebooks covering NumPy basics through advanced AI use cases
- Topics: array operations, indexing, broadcasting, linear algebra, random numbers
- Practical examples drawn from real AI/ML workflows
requirements.txtfor easy environment setup
- Python 3.8+
- Jupyter Notebook or JupyterLab
git clone https://github.com/hereandnowai/numpy-for-ai.git
cd numpy-for-ai
pip install -r requirements.txt
jupyter notebookOpen any notebook in Jupyter and run cells top to bottom:
Introduction to Numpy.ipynb— start here for the fundamentals1-basics-of-numpy.ipynb— core array operationsNumpy Operations.ipynb— advanced operations for AI/ML
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