ML NEWS - 181008


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Data science and machine learning in an industrial context
Data-driven modelling will complement and in some cases replace physical and engineering-based models through access to vast amounts of data combined with increased processing power and new modelling techniques. This will enable us to derive models from patterns and signals in the data itself, as opposed to being limited to making assumptions about how assets perform in the real world. The main outcomes will be the ability to automate a whole range of processes, to detect anomalies at a much earlier stage, simulate the impact of operational scenarios and to predict future states and events. It will surely contribute significantly to making industry more efficient, much safer and reduce its environmental impact.

Why building your own Deep Learning Computer is 10x cheaper than AWS
If you’ve used, or are considering, AWS/Azure/GCloud for Machine Learning, you know how crazy expensive GPU time is. And turning machines on and off is a major disruption to your workflow. There’s a better way. Just build your own Deep Learning Computer. It’s 10x cheaper and also easier to use.

Machine learning is already transforming the business world
A few decades ago, terms like “neural networks” – a computer system which is modelled on the human brain and nervous sytem – could be heard only in specialised academic circles, but these days this is one of the most popular buzzwords in the modern IT industry. Due to technological advancement, the cost of hardware has significantly decreased and so storing and processing data is now affordable for the masses. Moreover, the ways in which this data can be mined, applied and utilised have evolved. As a result, organisations are finding new ways of overcoming problems and innovating on a practical level – thus transforming the business world in ways that people 10 years ago could only ever imagine.


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