What do you think of when you hear “artificial intelligence”? Perhaps self-driving cars, autonomous robots, and Siri, Alexa or Google Home? But it doesn’t have to be that complex. You can build a powerful image classification model within a topic that inspires and interests you - with 3 easy steps.

How difficult is it to build your own intelligent application?  First, find a topic that interests you; it can be something that inspires you, excites you or a super simple day-to-day problem you’re facing. Which of your skills are matching your interests and other topics that excite you? Use that skill set to the next step, which is creating your own data.

My day-to-day repetitive problem was the daily makeup routine; it takes time and its quite uninspiring but when you finally decide to try something new - you literally get over 30 million results when search for “makeup tutorial” on Youtube and beauty being a $400 billion industry indicates that makeup plays a significant part of people’s lives. How do you even know what makeup style will look as good on you as it does on all the YouTubers?

Therefore I built my very first machine learning algorithm which tells you which eye shape you have and suggests makeup styles matching your particular eye shape to enhances your features. You just snap a photo of your eyes in the app, and the algorithm does the rest; telling you which eye shape you have and what makeup style that suits your particular eye shape. I build this app with 3 easy steps, and I’m excited to show how you can build yourself an own powerful image classification model, with your own data, within a topic that inspires and interests you. It might sound difficult, but I can’t wait to show you how few lines of Python you need to build the whole app.

What repetitive and categorizing tasks are you regularly facing? Bring your interests, passion and everyday problems, and we’ll explore a more widespread adoption of artificial intelligence solutions.


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Eric Mann at 14:09 on 26 Aug 2019

Stellar example of Keras in practice and an amazing intro to convolutional network architecture. The live demo at the end helped further illustrate both the journey to building an application and the speed at which a production application runs. Would love to see the talk made longer with further code examples and maybe a direct walkthrough of building a system from scratch, but otherwise the talk is fantastic as-is!