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When Philosophy and Python COLLIDE! - Part 2
Episode 16
Published 7 years, 2 months ago
Description
Sean and Kelly continue their conversation about the philosophy and ethics of machine learning and artificial intelligence in Python. This episode focuses more on resources and tools for AI learning after last episode's focus on philosophy and ethics.
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- Patreon: Want to hear more episodes from Kelly and Sean? Support us on Patreon so we can hire an audio editor!
Links:
- What is Amazon Machine Learning? - Amazon Machine Learning — Amazon Machine Learning (Amazon ML) is a robust, cloud-based service that makes it easy for developers of all skill levels to use machine learning technology.
- Build a PID Controller with Python – Onion — This week we‘ll be learning how to build a PID Controller using Python, the Omega2, and our recently released ADC Expansion. We’re going to use our PID Controller to keep an incubator at a constant temperature, but this setup can be easily modified and the code reused for your own purposes!
- The Difference Between YouTube’s Automatic Captions, DIY Captions, and 3Play Media Captions – 3Play Media — Have you ever watched a seemingly innocuous video with YouTube’s automatic captions? If not, go check it out.
- Experiments with style transfer — Style transfer is the technique of recomposing images in the style of other images. These were mostly created using Justin Johnson’s code based on the paper by Gatys, Ecker, and Bethge demonstrating a method for restyling images using convolutional neural networks.
- New Sims - PhET Simulations — By converting our sims to HTML5, we make them seamlessly available across platforms and devices. Whether you have laptops, iPads, chromebooks, or BYOD, your favorite PhET sims are always right at your fingertips.
- New App Makes It Easier to Colorize Old Photos | Smart News | Smithsonian — The software combines human input and a sophisticated neural network to make historical images pop
- Jason Yosinski — Deep neural networks have recently been producing amazing results! But how do they do what they do? Historically, they have been thought of as “black boxes”, meaning that their inner workings were mysterious and inscrutable. Recently, we and others have started shinning light into these black boxes to better understand exactly what each neuron has learned and thus what computation it is performing.
- Convolution -- from Wolfram MathWorld — A convolution is an integral that expresses the amount of overlap of one function as it