bqplot Seamless Interactive Visualizations and Dashboards in the Jupyter Notebook | SciPy 2018

We will then go over bqplot's library of statistical and machine learning focused higher level abstractions and tools which
are built to aid a Data Scientist or a Machine Learning researcher to interactively analyze the data, and arrive at useful insights. The seamless interactivity enables the creation of custom visualizations that allow researchers to understand their models and data in a much richer fashion.

The talk will also cover bqplot's seamless integration with the numerous other libraries in the Jupyter widgets ecosystem such as ipyleaflet or ipyvolume. We will then explain how to link these widgets together using callback functions and share a few examples of advanced applications from various disciplines built using other open source projects. We will wrap up by previewing the latest features we are adding to bqplot.

[thirdreplicator]

Amazing work. Sylvain should have gotten a standing ovation.

[TScottClendaniel]

Are the Jupyter notebooks available for download for those of us who couldn;t attend? (Please forgive me in advance if you answered this in the video and I just missed it- thank you!)

[maloxi]

People looking for the notebooks can find them here:

[dhristovaddx]

Great video. Is there some way I can download the notebooks?

[theodor-alexandrutufa]

Hello, great tutorial indeed. I am having troubles getting the dynamic sliding bars or any feature of ipywidgets. When I execute the code the output is: <function __main__.f(x)> Can anyone please help me overcome this? thanks