Jabil provides advanced manufacturing solutions that require visual inspection of components on production lines. Their pilot with Azure Machine Learning and Project Brainwave promises dramatic improvements in speed and accuracy, reducing workload and improving focus for human operators.
Proud to be the lead architect working on advanced Machine Learning solutions and pipelines at Jabil.
Sometimes working on advanced technologies comes with the peril of NDAs … which limit what I can talk about… but it is nice to see yet another of our projects feature in Keynote speech by Satya Nadella, this time at Microsoft //BUILD 2018. Proud to be the lead architect working on advanced Machine Learning solutions and pipelines at Jabil.
GitHub partnered with O’Reilly Media to examine how data science and analytics teams at several data-driven organizations are improving the way they define, enforce, and automate development workflows.
Download this complimentary book from: – https://resources.github.com/whitepapers/data-science/
Visualize business process workflows, real-world layouts like factory floor plans, network diagrams, organization structures or any illustration created in Microsoft Visio and easily connect it to Power BI data. Contextually represent Power BI data as colours or text on Visio diagrams. Now drive Operational Intelligence effectively using Visio custom visual.
Microsoft is making a cloud service that uses artificial intelligence to track down bugs in software generally available, and it will begin offering a preview version of the tool for Linux users as well.
Microsoft Security Risk Detection, previously known as Project Springfield, is a cloud-based tool that developers can use to look for bugs and other security vulnerabilities in the software they are preparing to release or use. The tool is designed to catch the vulnerabilities before the software goes out the door, saving companies the heartache of having to patch a bug, deal with crashes or respond to an attack after it has been released.
A free course and introduction to deep learning through the applied task of building a self-driving car. Taught by Lex Fridman.
Visit http://selfdrivingcars.mit.edu/ for full details of “MIT 6.S094: Deep Learning for Self-Driving Cars“.