Topics
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Computer Vision in Python: How to build a basic face detection system
By: Jeremy Watt
Length: 25 Minutes
Description: In this short talk Jeremy will describe the universal pipeline for performing object detection (that is, the automatic detection of objects in digital images) in Python. This will include a discussion of various classification schemes, feature extraction methods, and their fusion in the form of deep neural networks. Demo code illustrating these concepts will be shown using the IPython notebook environment. -
Getting meaningful results from unit tests
By: Manu Phatak
Length: 10 Minutes
Description: We count on unittests failure messages to give us reasonable feedback on how to proceed with a failing test. When you're working with builtin data structures and objects, unit test feedback is usually pretty good. It helps you identify and solve the problem. In contrast, the default results you get from custom objects can be practically useless. https://gist.github.com/bionikspoon/2e434a2c193a06b0996cc98c6a604de9 -
Intro to Deploying Django with Ansible
By: Joe Jasinski
Length: 15 Minutes
Description: Deploying Django is a breeze when using Ansible. Learn a bit about the power that Ansible provides and how easy it is to get started using it!