How Credit Suisse uses Python.

How Deloitte uses Python within the Enterprise Science Team.

First, I’ll discuss a data-gathering pipeline that uses AWS Lambda functions written in Python to scrape CTA’s BusTracker prediction service and interpolate actual arrival times. Then I’ll detail an API written in Django REST Framework to select and analyze a range of data. Finally, a simple JavaScript-based front-end visualizes the data provided by the API.

This is a brief overview depicting where I started before this mentorship, through the various projects me and Ray worked on, and where I plan to take it moving forward!

We have created a dataset from the search queries provided by Google and matched it up with some market data. We will attempt to produce a some metric or predictive model given the limited, slightly correlated data.

(Lightning talk as part of ChiPy mentorship) I'll be talking about using Python to develop a classifier for a Kaggle competition looking at crime data in San Francisco

This presentation will cover the Django project I completed with my mentor, Adam Bain. The idea for this project came from my former work as a caregiver for a child with Autism. As a caregiver, there were many times behavioral issues came up and I often wondered what other possible interventions people may have tried. The child I worked with was nonverbal which made discipline and finding out the source of a behavior much trickier. Every case of Autism is different but there are still some behaviors which are more common, especially as a result of the inability to communicate. For example, self-injurious behaviors are common and usually associated with the frustration of not being able to communicate needs. My idea is to create an app where caregivers are able to share their solutions to behavior problems and search for other caregiver’s solutions as well. The app will have a space for people to share both problem behaviors they want to decrease in their client or child and positive behaviors they want to encourage. This project allows caregivers to search for problem behaviors as well as positive behaviors and find out how other caregivers addressed the behavior and whether those interventions were successful or not.

Seeing as this winter marks 20 years of my using Python, I might be inclined to say a few short words about imposter syndrome.

Project Goal: Create an interactive dashboard using Django, featuring data table and chart which take customized user filtering and sorting and return the filtered result. Progress: 1. Data normalization 2. Data Importer 3. url patterns 4. Django form - HTTP get/post request 5. Created chart view with C3.js 6. Bootstrap for error warning and numeric stepper 7. Manipulate data within shell

The Portable Format for Analytics (PFA) (www.dmg.org) is an emerging standard for predictive analytics that addresses some of the limitations of the Predictive Model Markup Language (PMML) and was designed for today’s big data environments, including Hadoop, Storm and Spark. In this talk, I give an introduction to PFA, model deployment, and Titus: Open Data's Python toolkit for building, inspecting, and modifying PFA scoring engines. Robert Grossman is the Founder and a Partner at Open Data Group, which has building predictive models over big data for its clients since 2002. He is also a Professor in the Division of Biological Sciences at the University of Chicago, where he leads a research group in bioinformatics with a focus in managing and analyzing large genomic datasets for advancing the understanding of human disease.