Machine learning

Algorithms that independently learn to make predictions and decisions after training on datasets instead of being explicitly programmed.

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26 September 2019
6 min read
While consumer-facing applications of machine learning (ML) have gotten a lot of attention (Netflix, Uber, and Amazon) the back office deserves some recognition. Enterprise-level systems that run the business—think finance, robo-advisors, accounting, operations, human resources, and procurement—tend...
19 September 2019
3 min read
Continuous Integration and Continuous Deployment (CI/CD) are key components of any mature software development environment. During CI, newly added code is merged into the codebase, kicking off builds and automated testing. If all tests succeed, then the CD phase begins, deploying the changes automatically...
23 August 2019
6 min read
In software development, it makes sense to create reusable, portable, self-contained modules that can seamlessly plug into any application. As the old adages insist: rely on modular design, don’t repeat yourself (DRY), and write once, run anywhere. The rise of API-first design, containerization, and...
15 August 2019
3 min read
Are you an experienced fullstack developer looking to bring machine learning to your apps? Or are you an ML expert who wants to build a website to have a place to show off your models? In any event, the process of bringing AI to applications can be laborious and confusing—but it doesn’t have to...
9 August 2019
5 min read
As companies begin developing use cases for machine learning, the infrastructure to support their plans must be able to adapt as data scientists experiment with new and better processes and solutions. Concurrently, organizations must connect a variety of systems into a platform that delivers consistent...
5 July 2019
8 min read
Developing processes for integrating machine learning within an organization’s existing computational infrastructure remains a challenge for which robust industry standards do not yet exist. But companies are increasingly realizing that the development of an infrastructure that supports the seamless...
21 June 2019
5 min read
“Our machine learning infrastructure is a great big Frankenstein of one-offs,” said one data scientist at our Seattle Roadshow. Heads nodded. Every time his data-driven organization needs to integrate with a new system, software development teams hardcode dependencies and schedule jobs inside their...
13 June 2019
2 min read
We spend a lot of time focused on giving data scientists the best experience for deploying their machine learning models. We think they should not only use the best tools for the job, they should also be able to integrate their work easily with other tools. Today we’ll highlight one such integration:...
1 May 2019
4 min read
Every quarter, we talk with more than a hundred companies working to productionize their machine learning. We see a clear path out of the stage many companies cannot get past: operationalizing the model deployment process. The problem Massive effort goes into any well-trained model—research shows that...
14 March 2019
3 min read
Algorithmia developers unveiled a new UI on our user platform this week. Now, when you log into Algorithmia, you’ll see a personalized dashboard with your account information and recent activity, enabling easy account management and navigation. This change comes about as we mark the four-year anniversary...