KUALA LUMPUR, April 3 (Bernama) -- Bursa Malaysia ended lower today, with the benchmark index declining 0.5 per cent, weighed down by selected heavyweights led by Press Metal, IHH Healthcare, and Tenaga Nasional. Press Metal shed 16 sen to RM4.87, IHH Healthcare dipped 14 sen to RM6.75, and TNB slipped 18 sen to RM13.58. These stocks resulted in a 6.12-point decline in the benchmark index. At 5 pm, the FTSE Bursa Malaysia KLCI (FBM KLCI) slid 7.61 points to 1,518.91 versus Wednesday’s close of 1,526.52. The benchmark index opened 9.22 points lower at 1,517.30 and fluctuated between 1,512.32 and 1,524.41 throughout the day. In the broader market, losers thumped gainers 548 to 357, while 448 counters were unchanged, 994 untraded and eight suspended. Turnover rose to 2.51 billion units valued at RM1.81 billion against Wednesday’s 2.37 billion units valued at RM2.03 billion. ...
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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