A practical, hands-on guide to using machine learning in your Django projects, including a live demo of four applications. Machine Learning is probably the most important development in our industry (and possibly our civilisation!). Previously restricted to math geniuses with access to supercomputers and massive data centres, machine learning tools are increasingly available as web services which are easily consumed from more traditional web applications. Python has become the lingua franca of machine learning, so Django developers are well placed to take advantage of the next wave of application development. In this talk I’ll outline the various machine learning platforms and provide a set of practical examples that demonstrate how Django developers can start taking advantage of artificial intelligence in their own applications. These will include: Image recognition - using Microsoft Azure Vision to automatically caption and label the images your users upload Entity analysis - using the Google Cloud Natural Language API to tag news articles with people, locations and events Predictions - using Amazon Machine Learning to build a ‘you may also like’ feature Sentiment analysis - using IBM Watson to understand the tone of comments submitted to your site