Interactive Data Visualizations – Toll-Free Solutions
Data Visualization is the last step to the success with customer. Good visualization wouldn’t help incorrect analysis, but badly done visualization with perfect analysis can easily spoil the outcomes. In many cases static charts/graphs are not enough for the end-user. Along with story telling, this tools can be used to gather user input – labeling data for (semi)supervised-learning.
I will guide you through the possible open-source interactive solutions and their appropriate usage. Three main approaches would be covered:
– custom web application (Flask + d3.js);
– frameworks (Bokeh, Dash);
– iPython Widgets;
– BI solution (Apache Superset).
This approaches would be compared based on my experience working with them. A comparison to enterprise-level tools (Spotfire, Tableau) would be also made.
My talk would be focused on practical usage of Open-source Data Visualizations frameworks
Senior Data Scientist, GE Healthcare
Valentin Mikhaylenko is Senior Data Scientist at GE. He has worked on different analytical projects: Text Mining, Predictive Maintenance, Labor Optimization, Chatbot.
Prior to that, Valentin was software developer in automated stock trading company (High Frequency Trading) for 7 years building the whole trading platform from scratch, that made company profitable on Moscow Stock Exchange, and Data Scientist in Natural Language Processing startup for 2 years.
He graduated summa cum laude from ITMO University (Saint Petersburg, Russia) with a MSc in Applied Mathematics and Informatics. Also Valentin graduated from Borland Academy (AMSE, supported by Yandex and Jetbrains).