When it comes to Machine Learning it can be hard to find small scale real world applications that deliver good results.
To find such an application I challenged myself to build a Naive Bayesian tweet classifier. Classifying the author of any given tweet as President Obama or President Trump respectively, resulting in 98% accuracy!
This talk will go through scraping the data, building the classifier (without 'recoding the wheel') and showing how the model was verified.
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Building a Trump/Obama Tweet Classifier with 98% accuracy in 1 hour!
Ben Ellerby is an AWS Serverless Hero and VP of Engineering for Theodo. He is the editor of Serverless Transformation: a blog, newsletter, and podcast which share tools, techniques, and use cases for all things Serverless. He co-organizes the Serverless User Group in London and regularly speaks about Serverless around the world. At Theodo, Ben works with both new startups and global organisations to deliver digital products, training, and digital transformation with Serverless across London, Paris, and New York.