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Learn the theory of linear algebra hand-in-hand with the practice of software library development.

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LAFF

Linear Algebra Intro to LAFF Foundations to Frontiers

LAFF is a collection of resources designed to teach the theory of linear algebra hand-in-hand with the practice of software library development.

Contents of this document

Resources

  • e-book - The primary resource in PDF format.
  • mooc - Self-paced online course hosted on the edX platform.
  • videos - 270+ short videos hosted on YouTube.
  • notebooks - Programming assignments with their corresponding answer-keys. They are organized week-by-week in this repository and can be previewed using Jupyter's online Notebook viewer.
  • python library - A small software library of vector and matrix operations.
  • app - Self-contained software platform that allows interacting with the notebooks documents via a web browser. The Notebooks contain both executable python code and rich text elements.

Features

  • The software application has been preconfigured to work out of the box on all major operating systems.

  • The app was configured using miniconda and includes everything needed for the programming exercises. There's no need to install anything else Simply download, extract, and run.

  • The interactive programming Notebooks facilitate your learning as you connect the programming of vector and matrix operations to the mathematics of linear algebra.

Installation

Follow these download and setup instructions.

Contribute

  • Contribute code: Fix a bug, create a visualization tool, or add a new operation to the library.

  • Contribute non-code: Report an issue, translate the notebooks into your language, write a blog post about your learning experience, or give us feedback.

  • Let others know you are using these resources to learn linear algebra.

Support

If you are having issues, please let us know using the Issue Tracker.

Attributions Attributions

    ᔥ FLAME
    ᔥ Spark
    ↬ Probabilistic Programming and Bayesian Methods for Hackers

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Learn the theory of linear algebra hand-in-hand with the practice of software library development.

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  • Jupyter Notebook 98.2%
  • Python 1.8%