The tutorial videos from PyCon US 2014 are online! Talks to follow.
Tutorials arranged by author for your finding convenience:
- Blomo, Jim — mrjob: Snakes on a Hadoop
This tutorial will take participants through basic usage of mrjob by writing analytics jobs over Yelp data. mrjob lets you easily write, run, and test distributed batch jobs in Python, on top of Hadoop. Hadoop is a MapReduce platform for processing big data but requires a fair amount of Java boilerplate. mrjob is an open source Python library written by Yelp used to process TBs of data every day. - Clifford, Williams, G. — 0 to 00111100 with web2py
This tutorial teaches basic web development for people who have some experience with HTML. No experience with CSS or JavaScript is required. We will build a basic web application using AJAX, web forms, and a local SQL database. - Grisel, Olivier; Jake, Vanderplas — Exploring Machine Learning with Scikit-learn
This tutorial will offer an introduction to the core concepts of machine learning, and how they can be easily applied in Python using Scikit-learn. We will use the scikit-learn API to introduce and explore the basic categories of machine learning problems, related topics such as feature selection and model validation, and the application of these tools to real-world data sets. - Love, Kenneth — Getting Started with Django, a crash course
Getting Started With Django is a well-established series of videos teaching best practices and common approaches for building web apps to people new to Django. This tutorial combines the first few lessons into a single lesson. Attendees will follow along as I start and build an entire simple web app and, network permitting, deploy it to Heroku. - Ma, Eric — How to formulate a (science) problem and analyze it using Python code
Are you interested in doing analysis but don’t know where to start? This tutorial is for you. Python packages & tools (IPython, scikit-learn, NetworkX) are powerful for performing data analysis. However, little is said about formulating the questions and tying these tools together to provide a holistic view of the data. This tutorial will provide you with an introduction on how this can be done. - Müller, Mike — Descriptors and Metaclasses – Understanding and Using Python's More Advanced Features
Descriptors and metaclasses are advanced Python features. While it is possible to write Python programs without active of knowledge of them, knowing how they work provides a deeper understanding about the language. Using examples, you will learn how they work and when to use as well as when better not to use them. Use cases provide working code that can serve as a base for own solutions. - Vanderplas, Jake; Olivier Grisel — Exploring Machine Learning with Scikit-learn
This tutorial will offer an introduction to the core concepts of machine learning, and how they can be easily applied in Python using Scikit-learn. We will use the scikit-learn API to introduce and explore the basic categories of machine learning problems, related topics such as feature selection and model validation, and the application of these tools to real-world data sets.
Tutorials or talks with multiple authors are listed under each author. (I don’t know which one you will remember.)
I am going to spin up the page for the talks so when the videos appear, all I need do is to insert the video links.
Enjoy!