KUALA LUMPUR, June 18 (Bernama) -- Bursa Malaysia’s key index finished marginally higher, supported by strong buying interest in consumer-related counters, amid mixed performance across regional markets. At 5 pm, the FTSE Bursa Malaysia KLCI (FBM KLCI) rose by 1.40 points, or 0.08 per cent, to 1,711.39 from Tuesday's close of 1,709.99. The key index opened 12.36 points firmer at 1,722.35 and moved between 1,711.31 and 1,722.63 throughout the session. Market breadth was negative, with losers leading gainers 678 to 493, while 549 counters were unchanged, 1,016 untraded and 34 suspended. Turnover increased to 4.50 billion units worth RM3.45 billion from 3.93 billion units worth RM3.45 billion on Tuesday.
If you think Microsoft's new CEO is making another bold statement without action, think again. Microsoft's new CEO, Satya Nadella is serious about cloud computing and he has a strategy.
A supposedly comprehensive predictive analysis service — and all you have to do is store your data in Azure, the Microsoft cloud.
The service will be known as Microsoft Azure Machine Learning (ML) was announced on Monday but will only be available in June. This is the first time where Microsoft combines their very own software with publicly available open source software, so that it's much more easier for usage than most of the available arcane strategies that are available now.
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| Machine Learning - fixing today's problem yesterday |
The VP for ML at Microsoft proudly said, "This is drag-and-drop software."
This is a big step forward in popularizing what is currently a difficult process in increasingly high demand. It would also further the ambitions of Satya Nadella, Microsoft’s chief executive, of making Azure the center of Microsoft’s future.
Machine learning computers examine historical data through different algorithms and programming languages to make predictions. The process is commonly used in Internet search, fraud detection, product recommendations and digital personal assistants, among other things.
As more data is automatically stored online, there are opportunities to use machine learning for performing maintenance, scheduling hospital services, and anticipating disease outbreaks and crime, among other things. The methods have to become easier and cheaper to be popular, however.
That is the goal of Azure Machine Learning.
Here is a video posted by Microsoft on Youtube:
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