Interactive Machine Learning: Make Python 'Lively' Again

You have coded in Jupyter, the ubiquitous notebook platform for coding and testing cool ideas in virtually all major programming languages. You love it, you use it regularly. Project Jupyter was born out of the IPython Project in 2014 and evolved rapidly to support interactive data science and scientific computing across all major programming languages. There is no doubt that it has left one of the biggest degrees of impact on how a data scientist can quickly test and prototype his/her idea and showcase the work to peers and open-source community. However, learning and experimenting with data become truly immersive when user can interactively control the parameters of the model and see the effect (almost) real-time.