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Machine Learning

▾ 1 MINUTE READ — CLOSE

Machine learning moves beyond the traditional model of computation. Instead of arriving at a definite reproducible answer through a series of calculations, machine learning — a branch of artificial intelligence — works instead on a series of statistical probabilities to suggest new solutions to a problem. This work is useful for such jobs as designing new materials, medical diagnosis, advanced game graphics, and so many other tasks.

Much of the early success in machine learning has come from supervised learning, where a clearly defined data set is already available for analysis. But work has been going on to move beyond this model, with the Reinforcement Learning, where an agent learns by interacting with its environment. Gathering even more momentum has been Deep Learning, which doesn’t require all the intermediate steps that supervised learning does. Instead, the idea is to let the Deep Learning neural nets find the answers on their own.

At The New Stack, we have focused our coverage of this emerging field mostly around two areas of scalable architecture. We are keeping a close eye on an emerging field of AIOps, where machine learning can influence and drive IT operations. AIOps should be able to help by automating the path from development to production, predicting the effect of deployment on production and automatically responding to changes in how the production environment is performing. Companies such as New Relic, OpsRamp, and Moogsoft have all invested heavily in this area,

Another area of machine learning we are covering closely is how Kubernetes and related cloud native technologies can expedite the machine learning lifecycle.  Machine learning involves an entire IT cycle of technologies that are very early on in terms of productization: Data must be harvested and cleansed, models must be tested and the most useful models must be pressed into production, with a feedback loop of some sort to ensure the models can be updated. Emerging workflows such as Kubeflow and Anaconda can help streamline these processes.


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Development / Machine Learning

The Blueprint for Developers to Get Started with Machine Learning

13 Feb 2018 11:46am, by Janakiram MSV

Machine Learning / Microservices

Bonsai CEO Mark Hammond: Can Stateless Services Produce an AI?

12 Feb 2018 1:52pm, by Scott M. Fulton III

Development / Machine Learning / Open Source

This Week in Programming: Embracing That Thing Everyone Else Is Talking About

10 Feb 2018 6:00am, by Mike Melanson

Machine Learning

How AI and Laser-Shooting Robots Can Boost Productivity in the Construction Industry

8 Feb 2018 11:00am, by Kimberley Mok

Development / Machine Learning

This Week in Programming: Rust’s Roadmap for an Epoch Release

3 Feb 2018 6:00am, by Mike Melanson

Machine Learning

This Robot Can Visualize Its Immediate Future with Deep Learning

1 Feb 2018 11:00am, by Kimberley Mok

Development / Machine Learning

It’s Go Time: Stream 2.0 Ditches the Pokey Python in Favor of the Faster GoLang

30 Jan 2018 6:00am, by Michelle Gienow

Machine Learning / Contributed

5 Essential Pieces of the Deep Learning Puzzle

29 Jan 2018 9:00am, by Scott Clark

Machine Learning / Security

This Week in News: Meet Your New Pair-Programming Partner

26 Jan 2018 2:00pm, by TNS Staff

Culture / Development / Machine Learning

Code n00b: Hail, Web Development Robot Masters!

26 Jan 2018 12:00pm, by Michelle Gienow

Culture / Edge / IoT / Machine Learning / Serverless

Tutorial: Anomaly Detection in Connected Devices with PubNub and Azure Machine Learning

26 Jan 2018 6:00am, by Janakiram MSV

CI/CD / Data / Development / Machine Learning

Codota Offers Pair Programming with Artificial Intelligence

25 Jan 2018 6:00am, by Alex Handy

CI/CD / Cloud Native / Culture / Data / Edge / IoT / Machine Learning

Computes Aggregates Idle CPUs to Create Decentralized Supercomputer

25 Jan 2018 3:00am, by Susan Hall

Machine Learning

IBM, Intel Rethink Processor Designs to Accommodate AI Workloads

23 Jan 2018 9:14am, by Agam Shah

CI/CD / Containers / Kubernetes / Machine Learning

AppLariat Provides on-the-fly Container Reconfiguration

22 Jan 2018 8:13am, by Susan Hall

Development / Machine Learning / Serverless

This Week in Programming: Oops, I Clicked The Wrong Link and Set Off a Nuclear Scare

20 Jan 2018 6:00am, by Mike Melanson

Culture / Edge / IoT / Machine Learning / Serverless

Implement IoT Predictive Maintenance with PubNub and Azure Machine Learning

19 Jan 2018 6:00am, by Janakiram MSV

Development / Machine Learning

Google AI Achieves “Alien” Superhuman Mastery of Chess and Go in Mere Hours

18 Jan 2018 11:00am, by Kimberley Mok

Data / Edge / IoT / Machine Learning

MapR: How Next-Gen Applications Will Change the Way We Look at Data

11 Jan 2018 1:35pm, by Swapnil Bhartiya

Data / Machine Learning / Serverless

Learning to Rank: A Key Information Retrieval Tool for Machine Learning Search

9 Jan 2018 3:00am, by Mary Branscombe

API Management / CI/CD / Data / Development / Machine Learning

This Week in Programming: A Non-Inclusive Retrospective of Times Past

6 Jan 2018 6:00am, by Mike Melanson

Machine Learning / Tools

Source{d} Applies Machine Learning to Help Companies Manage Their Code Bases

2 Jan 2018 9:00am, by Susan Hall

CI/CD / Cloud Native / Cloud Services / DevOps / Machine Learning

Sam Ramji Talks Developer Experience for Google Cloud

28 Dec 2017 6:44am, by Alex Handy

Machine Learning

Run the JeVois Smart Machine Vision Algorithms on a Linux Notebook

27 Dec 2017 10:45am, by drtorq

Machine Learning

How Brain-Computer Interfaces Could Expose Us to Hacking and Manipulation

25 Dec 2017 12:30pm, by Kimberley Mok

Development / Machine Learning / Contributed

Poodle, Pug, or Wiener Dog? Deploy a Dog Identification TensorFlow Model Using Python and Flask

22 Dec 2017 9:00am, by Pete Garcin

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