Lecture: Practical machine learning for everyday web apps
Making TensorFlow the brain of your Django app
A new wave of machine learning is in full swing. This talk gives an overview of the modern Python machine learning stack based on TensorFlow and my practical experiences from using it in a typical Django web app.
You've probably heard of the recent buzz surrounding deep learning, self-driving cars, Amazon Echo's speech interface, Google DeepMind's AlphaGo program beating a human Go master… The modern applications of machine learning are exploding! But can you benefit from the advances in AI in your everyday web apps? How much data do you need to be able to solve some concrete classification problems? What sort of machinery do you need to run it?
This talk will give an overveiw of Google's recently open sourced TensorFlow library and how it can be used for machine learning. To keep things grounded to realistic problems, we will go through an example Django web app for finding events where we want to classify images based on their content. We'll show how to train the desired image classifier using TensorFlow and use it to classify unknown images. We'll also cover the sort of infrastructure you need to use TensorFlow and give an overview of the available cloud services with specialised hardware support for high performance use cases.