Posts byAlgorithmia
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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,...
2 July 2018
4 min read
Slack is one of the fastest growing companies of all time, and there’s a good chance it’s also the messaging app that you use for work. The Algorithmia Slack Client lets you integrate Machine Learning into your Slack channels – both as slack commands and as bot users – giving you more firepower...
27 June 2018
4 min read
Source: Wikipedia Despite only making it into the political mainstream recently, crowd size estimation has always been an important task for corporate development, retail planning, and resource allocation. It helps property owners and event organizers predict demand, understand utilization of physical...
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...
25 June 2018
9 min read
Source: KDnuggets How to version control your production machine learning models Machine learning (ML) is about rapid experimentation and iteration, and without keeping track of your modeling history you won’t be able to learn much. Versioning lets you keep track of all of your models, how well they’ve...
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...
29 May 2018
9 min read
Source: turnoff.us Deploying machine learning models at scale is one of the most pressing challenges faced by the community of data scientists today, and as ML models get more complex, it’s only getting harder. The most common way machine learning gets deployed today is on powerpoint slides. We estimate...
14 May 2018
15 min read
We only understand a sliver of how the human brain works, but we do know that it often learns through trial and error. We’re rewarded when we do good things and punished when we do the wrong ones; that’s how we figure out how to live. Reinforcement learning puts computational power behind that exact...