Python

Building Data Apps with Python Workshop Returns on February 6th!

Building Data Apps with Python Workshop Returns on February 6th!

Data Community DC and District Data Labs are hosting another session of their Building Data Apps with Python workshop on Saturday February 6th from 9am - 5pm. If you're interested in learning about the data science pipeline and how to build and end-to-end data product using Python, you won't want to miss it. Register before January 23rd for an early bird discount!

Building Data Apps with Python Workshop Returns on June 6th

Building Data Apps with Python Workshop Returns on June 6th

Data products are usually software applications that derive their value from data by leveraging the data science pipeline and generate data through their operation. They aren’t apps with data, nor are they one time analyses that produce insights - they are operational and interactive. The rise of these types of applications has directly contributed to the rise of the data scientist and the idea that data scientists are professionals “who are better at statistics than any software engineer and better at software engineering than any statistician.”

These applications have been largely built with Python. Python is flexible enough to develop extremely quickly on many different types of servers and has a rich tradition in web applications. Python contributes to every stage of the data science pipeline including real time ingestion and the production of APIs, and it is powerful enough to perform machine learning computations. In this class we’ll produce a data product with Python, leveraging every stage of the data science pipeline to produce a book recommender.

Announcing the Publication of Practical Data Science Cookbook

Practical Data Science Cookbook is perfect for those who want to learn data science and numerical programming concepts through hands-on, real-world project examples. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of data science projects, the steps in the data science pipeline, and the programming examples presented in this book. 

Social Network Analysis with Python Workshop on November 22nd

Data Community DC and District Data Labs are hosting a full-day Social Network Analysis with Python workshop on Saturday November 22nd.  For more info and to sign up, go to http://bit.ly/1lWFlLx.  Register before October 31st for an early bird discount!

Social networks are not new, even though websites like Facebook and Twitter might make you want to believe they are; and trust me- I’m not talking about Myspace! Social networks are extremely interesting models for human behavior, whose study dates back to the early twentieth century. However, because of those websites, data scientists have access to much more data than the anthropologists who studied the networks of tribes!

Fast Data Applications with Spark & Python Workshop on November 8th

Data Community DC and District Data Labs are excited to be hosting a Fast Data Applications with Spark & Python workshop on November 8th  For more info and to sign up, go to http://bit.ly/Zhj0y1.  There’s even an early bird discount if you register before October 17th!

Hadoop has made the world of Big Data possible by providing a framework for distributed computing on economical, commercial off-the-shelf hardware. Hadoop 2.0 implements a distributed file system, HDFS, and a computing framework, YARN, that allows distributed applications to easily harness the power of clustered computing on extremely large data sets. Over the past decade, the primary application framework has been MapReduce - a functional programming paradigm that lends itself extremely well to designing distributed applications, but carries with it a lot of computational overhead.