Ml devops

How machine learning is reshaping the traditional software development lifecycle.

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11 September 2020
4 min read
A machine learning framework is an interface that allows developers to build and deploy machine learning models faster and easier. A tool like this allows enterprises to scale their machine learning efforts securely while maintaining a healthy ML lifecycle.
11 September 2020
4 min read
Just like any software, it’s important to keep machine learning models secure during development and production stages. Learn more from Algorithmia.
11 September 2020
6 min read
Model governance is the overall framework for how an organization controls their model development and deployment workflow. This includes setting the rules and controls for machine learning models in production, such as access control, testing, validation, and the tracing of model results.
10 September 2020
7 min read
Learn all about ML pipelines. How they benefit an organization and how you can implement this technology in your organization.
13 August 2020
8 min read
Learn about CI/CD pipelines, how they improve the software development lifecycle, and Algorithmia’s CI/CD solution for machine learning.
22 June 2020
4 min read
Today, mass amounts of data come from a myriad of applications and microservices. DevOps engineers are often tasked with ensuring that data is collected, retained, and secured in a way that follows strict regulations. Focusing on data security, many companies rely on VMware for various internal cloud-computing...
20 March 2020
4 min read
There is no doubt that more needs to be said about how time series data analysis advances DevOps. Time series classification is a tertiary aspect of time series data itself. By harnessing performance benefits from the powerful capabilities of a machine learning deployment platform, multiple types of...
13 February 2020
5 min read
Time series data, the key data points that have an associated timestamp allowing indexing in time order, are in most cases INSERT-intensive, requiring specialized time series databases as opposed to traditional relational practice as seen in SQL. Prior to advancements in machine learning, much of the...
2 January 2020
3 min read
DevOps Engineers are delighted when they find a product or service that fits in with their already refined CI/CD processes. When we choose a new pipeline tool, engineers depend on a number of factors. Ease of use, repeatable processes, and a solid support model are key. Choosing a continuous integration...
16 November 2017
8 min read
When Google’s Gradient Ventures invested in us, they did so with an understanding that it is incredibly hard to deploy AI/ML infrastructure — and that every dev team is going to need to solve this problem. Our solution, the AI Layer, is the best-in-class architecture.As our co-founder, Kenny...