With all the innovative applications and awesome educational resources that our community has been creating, we wanted to showcase some of our favorites to inspire you to start tinkering with machine learning technology. Here’s our roundup of the best of the best developer apps from July!
It can be pretty difficult to keep up with all the latest artificial intelligence and machine learning updates, and it’s even harder to grasp how you can actually put it all into practice. We find that it’s helpful to see real-world examples, so that’s why we pulled together this showcase of tangible applications that people are building. With that said, here’s how our community is shaking off the AI hype and delivering real-world results instead.
Ohhh, the Reddit culture. If you’re a part of it, you know it can be a great place to keep up with the internet and share meme-ingful content, but it can also be a place where “risky click” links are shared as well. For some, gore and nudity are not worth upvoting, which is why Sreenivas V Rao built the /u/RiskyClickerBot to help users automatically filter out images that are NSFW. If you want to know how he’s keeping Redditors more informed with image recognition, take a look at how he’s placing NSFW confidence scores next to the links.
Love pinning things to your furniture Pinterest board, but have trouble actually finding something similar to what you’re looking for? Well, West Elm’s new Pinterest Style Finder tool can help. Built on top of visual search, neural networks work to help identify the user’s personal aesthetic and returns similar items from the West Elm site. That means, relying on browser history is history! E-commerce sites can now recognize their customer’s preference in real-time and deliver hyper-relevant product recommendations.
If you think building a machine learning image recognition API is a daunting technical challenge, you’re right. It requires massive computational power, a team of experts, data scientists, lots of code/data, and a constant tweaking of parameters. That’s why we’re here to take care of all that heavy lifting for you so that you can focus on the core functionality of what you’re building instead. If you’re new to using image recognition, check out Sam Agnew’s tutorial on how to easy it is to build a Flask application in Python using Twilio MMS + Clarifai to receive picture messages over a phone number with relevant keywords.
Candid IO, a social discovery platform that helps brands discover powerful user-generated photos for their products, recently automated their workflows using Clarifai’s Visual Search product. To better provide marketers the tools they need to increase engagement from their fans, image recognition is making it even easier to deliver on-brand UGC. Now marketers using their platform have a greater opportunity to provide their customers with a more immersive brand experience.
Called one of the “best explanation(s) I’ve ever seen about neural networks and the convolutional layer!” by developer Adrien Joly, our very own Keeyon Ebrahimi sat down with our friends at dev.to to go over the ins and outs of convolutional neural networks. Once you listen to Keeyon’s explanation, you’ll wonder how we even existed before machine learning came about.
We’ve only scratched the surface of what you can do with machine learning technology and thanks to our easy-to-use API, there are endless real-world applications you can start building, too. If you want to learn more, connect with us on social @Clarifai or comment below with feedback – we’d be happy to chat or answer any questions you may have. And if you want to be featured in next month’s roundup, build something cool and share it with us!