Python-Powered Data Science at Civis
By: Stephen Hoover
Date: Feb. 11, 2016, 7 p.m.
Civis Analytics uses Python to develop the machine learning software which powers our products, and we run our Python software in production. I'll give a (very) brief overview of what Civis Analytics does and where Python and the open source community fit into the picture.
Python at Credit Suisse
By: David Matsumura
Date: Feb. 11, 2016, 7 p.m.
How Credit Suisse uses Python.
Python at Cofactor
By: Hector Rios
Date: Feb. 11, 2016, 7 p.m.
We are going to talk about our history -- a high level why we switched from .net to python.
Topics include .NET pain points and the reason why we chose Python. We looked at Ruby, and chose against Ruby.
We will also talk about how we use Python, which include Bottle + MongoDB to build our APIs.
Python at Vokal
By: Chris Foresman
By: Adam Bain
Date: Feb. 11, 2016, 7 p.m.
How Vokal uses Python with Adam Bain and Chris Foresman
Python at OptionsAway
By: Tim Saylor
Date: Feb. 11, 2016, 7 p.m.
How OptionsAway, an airfare lock startup, uses Python.
How SpotHero uses Python
By: Cezar Jenkins
Date: Feb. 11, 2016, 7 p.m.
SpotHero is one of the leading online parking reservation companies in the country. Come see how were using Python to make that happen.
Python at Modest
By: Emily Anderson
By: Mark Ashton
Date: Feb. 11, 2016, 7 p.m.
We will describe how Modest, recently acquired by Braintree (PayPal) uses Python.
Python at ShiftGig
By: Brian Eagan
By: Tyler Hendrickson
Date: Feb. 11, 2016, 7 p.m.
How ShiftGig, which connects the right people with the right job, uses Python.
Constructing a risk metric from google query data
By: Michael Tamillow
Date: Jan. 14, 2016, 7 p.m.
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.
Shuang Qiu
By: Shuang Qiu
Date: Jan. 14, 2016, 7 p.m.
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