If your neural nets are getting larger and larger but your training sets aren’t, you’re going to hit an accuracy wall. If you want to train better models with less data, I’ve got good news for you.
Dataset augmentation – the process of applying simple and complex transformations like flipping or style transfer to your data – can help overcome the increasingly large requirements of Deep Learning models. This post will walk through why dataset augmentation is important, how it works, and how Deep Learning fits in to the equation.
Source: Case Engineering
Diagnostics is part of the core of healthcare — research suggests a third of all Healthcare AI SaaS companies are tackling just this sector.
Machine Learning can automate parts of the diagnostic stack, aid doctors in deciding how to interpret tests, and greatly reduce errors in communication. This post will walk through popular use cases, the challenges inherent in applying ML models in diagnostics, and some of the tradeoffs to be made in model selection.
In this post, we’ll focus on potential use cases. We’ll start with a quick refresher on what this algorithm does, and then look at concrete examples of real world problems that this algorithm can tackle – and why it makes sense for you to give it go. Read More…
For every dollar of fraud that financial services companies suffer, they incur $2.67 in costs to their business. With more entry points in the digital age and increasingly sophisticated attackers, tackling fraud manually is quickly fading to irrelevance: but Machine Learning offers a promising way to automate the process, as well as surface more nuanced fraud patterns.
This post will walk through the challenges of applying ML models to fraud detection, popular applications, and tradeoffs to think about in model selection.
At Algorithmia we’re lucky enough to be surrounded by group of wildly intelligent, quirky, and fun engineers. We’d love for you to come by and meet them in person, but until then we’ll post a series of interviews introducing you to some of the talented people who are creating the future of AI.
For today’s installment, We’d like to introduce you to Besir! He’s an Algorithm Engineer who develops unique AI/ML algorithms. You may remember him from our work on the DanKu protocol, the first trustless contract on the ethereum blockchain. Fun fact: the Ku of DanKu is for Besir’s last name.