In an official announcement, Linus Torvalds confirmed that version 3.7 of the Linux kernel is now stable. It’s the first Linux kernel to have generic support for ARM-based processor architectures, making it easier to get Linux onto smartphones, tablets and gadgets like the Raspberry Pi.
For those not in the Linux / Unix loop, the “kernel” is the heart of any Linux (or open) operating system. Linux’s highly modular nature means that unlike in Windows or Mac, very clear distinctions are maintained between its components. The kernel handles the devices, processor, RAM and other core functions of an OS. On top of it go the various application platforms and user interfaces, which can be removed and re-inserted at will, so to speak.
Currently, every time a Linux-based system (eg: Android) is ported to an ARM processor, the developers have to write a new kernel for that processor’s particular architecture. Since there’s quite a lot of different processors floating around (Samsung’s Exynos, TI’s OMAP-4, and Qualcomm stuff, for instance) porting Linux-based operating systems across platforms is quite a tough task. The new kernel is expected to make that process shorter. It’s like the generic graphics drivers that Windows loads: it’s not pretty or optimized, but it lets you see enough to find and run that driver setup for your shiny new video card. This idea a bit similar to Microsoft’s new Windows, although not as functional: one base system that can run on any platform. One Kernel to Rule Them All. There’s also a heap of Human Interface Device additions that add multi-touch support and a whole list of game console controllers supported – yes, including the PS3’s BD controller.
Currently the support’s leaning more towards server and embedded device processors: Calxeda’s Higbank ARM server processor, Marvell’s ARMADA SoC processors, and Altera’s Cortex A9 design (Samsung Note and S2) are among the ranks. According to Torvalds, they’ll be adding in more supported processors within the next few releases.
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What kicked off in 2011 as a friendly gaming event has now developed into a fully-fledged gaming tournament. With the goal of promoting team building, leadership, and planning, the Virtusa
What kicked off in 2011 as a friendly gaming event has now developed into a fully-fledged gaming tournament. With the goal of promoting team building, leadership, and planning, the Virtusa LAN Challenge 2018 is happening.
Semi-Finals of the internal tournament will take place on the 22nd and 23rd of January 2018 at Virtusa premises.
january 22 (Monday) - 23 (Tuesday)
Virtusa Pvt. Ltd. 752, Dr Danister De Silva Mawatha, Colombo 09
The main purpose of the workshop is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use
The main purpose of the workshop is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning and big data.
Module 1: Introduction to Machine Learning
This module introduces machine learning and discussed how algorithms and languages are used.
· What is machine learning?
· Introduction to machine learning algorithms
· Introduction to machine learning languages
Module 2: Introduction to Azure Machine Learning
Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.
· Azure machine learning overview
· Introduction to Azure machine learning studio
· Developing and hosting Azure machine learning applications
Module 3: Managing Datasets
At the end of this module the student will be able to explore various types of data in Azure machine learning.
· Categorizing your data
· Importing data to Azure machine learning
· Exploring and transforming data in Azure machine learning
Module 4: Building Azure Machine Learning Models
This module describes how to use regression algorithms and neural networks with Azure machine learning.
· Azure machine learning workflows
· Using regression algorithms
· Using neural networks
Module 5: Using Azure Machine Learning Models
This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.
· Deploying and publishing models
· Consuming Experiments
Module 6: Using Cognitive Services
This module introduces the cognitive services APIs for text and image processing to create a recommendation application, and describes the use of neural networks with Azure machine learning.
· Cognitive services overview
· Processing language
· Processing images and video
· Recommending products
Feel free to contact us for any inquiries
uditha bandara – 0716092918
All Day (Wednesday)
ANC education ,310 R A De Mel Mw, Colombo 03 00300
Blue Chip Training0716092918
Startup Weekend is a global phenomenon - 54 hours of fast and furious prototype development through to exploring potential markets and pitching. It’s an unparalleled opportunity to build lasting relationships
Startup Weekend is a global phenomenon – 54 hours of fast and furious prototype development through to exploring potential markets and pitching. It’s an unparalleled opportunity to build lasting relationships with co-founders; mentors, and investors.
The real value comes from taking an idea from concept through to execution using Lean tactics and working under high pressure with the best startups.
26 (Friday) 5:00 pm - 28 (Sunday) 8:00 pm
Oak Ray Regency Kandy
Oak Ray Regency Kandy, No 9, Devani Rajasinghe Mawatha,, 20000 Kandy