Machine learning
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6 August 2018
6 min read
Source: TDS 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...
2 August 2018
7 min read
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 models can automate parts of the diagnostic stack, aid doctors in deciding how to interpret tests and reports, and greatly...
30 July 2018
6 min read
Source: TDS We recently went into detail about the Document Classifier algorithm in our spotlight. That’s all fine and good, but it’s not immediately clear what can you do with it. In this post, we’ll focus on potential use cases. We’ll start with a quick refresher on what this algorithm...
19 July 2018
4 min read
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...
10 July 2018
12 min read
As many applied ML practitioners know, productionizing ML tools can be deceptively difficult. At Algorithmia we’re always striving to make our algorithms the best in class, and we’ve recently made a series of performance and UX changes to our Document Classifier algorithm, and put work towards...
9 July 2018
4 min read
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. Today,...
27 June 2018
4 min read
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...
21 June 2018
8 min read
Source: TensorFlow Machine Learning is emerging as a serious technology just as mobile is becoming the default method of consumption, and that’s leading to some interesting possibilities. Smartphones are packing more power by the year, and some are even overtaking desktop computers in speed and reliability....
11 June 2018
7 min read
Source: Forgeahead Multi-cloud is quickly becoming the de facto strategy for large companies looking to diversify their IT efforts. At Algorithmia, we deploy across multiple clouds and recommend it for Machine Learning pipelines and portfolios. This post will outline the pros and cons of a multi-cloud...
6 June 2018
5 min read
Source: Timo Elliott Asking your Data Scientists to deploy their Machine Learning models at scale is like having your graphic designers decide which sorting algorithm to use; it’s not a good skill fit. The fact of the matter is that in 2018, the standard Data Science curriculum doesn’t prepare students...