Special thanks to Plotly investor, NVIDIA, for their help in reviewing these open-source Dash applications for autonomous vehicle R&D, and Lyft for initial data visualization development in Plotly.
Author: Xing Han Lu, @xhlulu
📌 To learn more about how to use Dash for Autonomous Vehicle and AI Applications register for our live webinar with Xing Han Lu, Plotly’s Lead AI/ML Engineer
Imagine eating your lunch, streaming your favorite TV shows, or chatting with your friends through video call inside the comfort of your car as it manages to drive you from home to work, to an appointment, or to a completely different city hours away. In fact, it would drive you through rain and snow storms, avoid potholes and identify pedestrians crossing the streets in low-light conditions; all this while ensuring that everyone stays safe. To achieve this, automotive manufacturers will need to achieve what is called “level 5 driving automation” (L5), which means that the “automated driving features will not require you to take over driving” and “can drive everywhere in all conditions”, as defined by SAE International. …
📌 Want to learn how to use Dash for Julia to build high-performance dashboards? Reserve your spot for our joint webinar on October 21st!
Today, we’re excited to officially welcome Dash for Julia. By adding Julia to Dash’s Python and R back ends, the Jupyter trinity is complete again.
“Dash is a productive Python framework for building web applications,” so starts Plotly’s Dash documentation. That is indeed how Dash began, allowing data scientists to build rich, beautiful, exploratory portals to their data using only Python. But, describing Dash as a Python framework misses a key feature of its design: the Python side (the back end/server) of Dash was built to be lightweight and stateless. …
📌 Learn how to deliver AI for Big Data using Dash & Databricks this recorded webinar with Peter Kim of Plotly and Prasad Kona of Databricks.