# talks

**Repository Path**: mirrors_markusschanta/talks

## Basic Information

- **Project Name**: talks
- **Description**: Slides and materials for various talks I've given
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-02-27
- **Last Updated**: 2026-06-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

This repository contains slides and accompanying materials for various talks I've given:

<table>
  <tbody>
    <tr>
      <th>Thumbnail</th>
      <th>Talk Title</th>
      <th>Description</th>
    </tr>
    <tr>
      <td width="25%"><a href="2022-12 - Awesome Jupyter - Talk Python Podcast"><img src="2022-12 - Awesome Jupyter - Talk Python Podcast/banner.png"></a></td>
      <td width="25%"><a href="2022-12 - Awesome Jupyter - Talk Python Podcast"><b>Awesome Jupyter Tools and Libraries - Talk Python Podcast</b></a></td>
      <td width="50%">This podcast episode of the Talk Python Podcast hosted by Michael Kennedy gives an overview of Awesome Jupyter, a curated list of awesome Jupyter projects, libraries and resources. </td>
    </tr>
    <tr>
      <td width="25%"><a href="2018-07%20-%20Vega%20-%20Full%20Stack%20Quants"><img src="2018-07 - Vega - Full Stack Quants/banner.jpg"></a></td>
      <td width="25%"><a href="2018-07%20-%20Vega%20-%20Full%20Stack%20Quants"><b>Vega – A Grammar of Interactive Graphics</b></a></td>
      <td width="50%">This talk gives an overview of Vega, a framework for interactive visualisation. It also includes a step-by-step tutorial for creating production-quality visualisations. Finally, I give an overview of related libraries and tools that you can use to create plots more easily.</td>
    </tr>
    <tr>
      <td width="25%"><a href="2018-03%20-%20JupyterLab%20-%20Full%20Stack%20Quants"><img src="2018-03 - JupyterLab - Full Stack Quants/banner.jpg"></a></td>
      <td width="25%"><a href="2018-03%20-%20JupyterLab%20-%20Full%20Stack%20Quants"><b>JupyterLab - Your Personal Data Science Workbench</b></a></td>
      <td width="70%">This presentation introduces JupyterLab as a data science/research environment and shows off its most useful features. It also includes instructions for setting up an instance of JupyterLab either locally or in the cloud on Amazon AWS.</td>
    </tr>
  </tbody>
</table>