<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/18a3a6dabff4404aaafd47b49d30f7ed&quot; frameborder=&quot;0&quot; width=&quot;1202&quot; height=&quot;901&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>901</height><width>1202</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>901</thumbnail_height><thumbnail_width>1202</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/18a3a6dabff4404aaafd47b49d30f7ed-14bb77bcce3dbfd1.gif</thumbnail_url><duration>313.0132</duration><title>Installing Sphinx on VS Code for Data Science 📊</title><description>In this video, I walked through the process of installing Sphinx on a fresh VS Code installation, which is applicable to other VS Code-based browsers as well. We set up a data science environment by installing the necessary extensions, including Python, Jupyter, and Sphinx itself. After creating a new notebook, I demonstrated how to interact with Sphinx, including logging in and configuring settings for personalized responses. I also highlighted the different modes available, such as Safe Mode and Plan Mode, to enhance user control and security. I encourage you to explore these features and customize Sphinx to fit your data science needs.</description></oembed>