You are viewing content from a past/completed QCon

Presentation: Jupyter Notebooks: Interactive Visualization Approaches

Track: Applied AI & Machine Learning

Location: Pacific LMNO

Duration: 4:10pm - 5:00pm

Day of week: Wednesday

Level: Intermediate

Persona: Backend Developer, Data Engineering, Data Scientist, Developer

Share this on:

This presentation is now available to view on InfoQ.com

Watch video with transcript

Abstract

Jupyter Notebooks are becoming the IDE of choice for data scientists and researchers. They provide the users with a nice exploratory environment where they can quickly research and prototype different models and visualize the results all in one place. Notebooks are easy to share and can be converted into documents/slides to present to stakeholders. 

With widget libraries like ipywidgets and bqplot, users can create rich applications, dashboards and tools by just using python code.

In this talk, we will see how we can build interactive visualizations in the Jupyter notebook. In the first part of the talk, I'll introduce the widget libraries and walk you through the code of a simple example so we understand how to assemble and link these widgets. Then we'll look at usecases including building dashboards from server logs, twitter sentiment analysis and finally tools for building, training and diagnosing deep learning models.

Speaker: Chakri Cherukuri

Senior Researcher in the Quantitative Financial Research Group @Bloomberg

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research group at Bloomberg LP. His research interests include quantitative portfolio management, algorithmic trading strategies and applied machine learning. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. Before that he worked in the Silicon Valley for startups building enterprise software applications. He has extensive experience in numerical computing and software development. He is a core contributor to bqplot, a 2D plotting library for the Jupyter notebook. He holds an undergraduate degree in engineering from Indian Institute of Technology, Madras and an MS in computational finance from Carnegie Mellon University.

Find Chakri Cherukuri at

Similar Talks

Machine Learning on Mobile and Edge Devices With TensorFlow Lite

Qcon

Developer Advocate for TensorFlow Lite @Google and Co-Author of TinyML

Daniel Situnayake

CI/CD for Machine Learning

Qcon

Program Manager on the Azure DevOps Engineering Team @Microsoft

Sasha Rosenbaum

ML in the Browser: Interactive Experiences with Tensorflow.js

Qcon

Research Engineer in Machine Learning @cloudera

Victor Dibia

Scaling Patterns for Netflix's Edge

Qcon

Playback Edge Engineering @Netflix

Justin Ryan

Machine Learning 101

Qcon

Data Scientist @IBM

Grishma Jena

ML/AI Panel

Qcon

Staff Developer Relations Engineer @Google Cloud Platform

Amy Unruh

Tracks

Monday, 11 November

Tuesday, 12 November

Wednesday, 13 November