Tag Archives: machine learning

Analytics at scale: what data analysts need to know

March 7, 2018

With every technology company shouting “Big Data”, we are led to think analytics challenges can be solved simply by storing a whole mess of data. With current technology, storing large volumes of data is easy. It also provides absolutely no value. Value only comes from data when it is examined, manipulated, learned from, and acted… Read More »

Spend more time on analytics and less on data prep

March 6, 2018

What are the things keeping analysts and data scientists from productivity?  According to studies, it’s wrangling data. Vast volumes of data need to be sourced, collected, organized and cleansed to be useful in solving problems.  In an article by Forbes, it is estimated that about 80 percent of the time spent working with data was… Read More »

What is the definition of AI?

March 5, 2018

Finally, here we are. After four posts discussing the differences between machine learning and AI, and demonstrating that AI can live without machine learning (and vice versa), the time has come to define AI. Easy, right? Not necessarily… Let us first point out that there is no committee to decide which products constitute an AI… Read More »

AI without machine learning

February 26, 2018

Previously, we explained how machine learning can have its own life and doesn’t need to be a part of AI. Here, we want to explain something that may surprise you: it is possible to build AI without machine learning. “A car with no engine!?” you may cry. Analogies are made to be broken. There are… Read More »

What is machine learning?

February 12, 2018

Every useful machine – from advanced AI through to the humble toaster – has to possess ‘knowledge’ about the world in which it operates. For example, within the design of a household toaster, much knowledge about the world must have already been implemented. This is implicit knowledge. The toaster ‘knows’ what electrical voltage is available… Read More »

Predictive Asset Maintenance: what are the business benefits – and how do we prove them?

February 6, 2018

With exponential digitalisation, asset management systems are becoming increasingly sophisticated, bringing new data sources and a data-driven approach. Weather data, asset information and sensor data from equipment can be integrated and given to machine learning algorithms to predict and prevent disruptions and failures. Ever sophisticated approaches enabled by new available data can help businesses to… Read More »

Wait, machine learning and artificial intelligence aren’t the same thing?

February 5, 2018

Everybody seems to be talking about artificial intelligence and machine learning. Ever since Spielberg’s 2001 movie A.I. Artificial Intelligence, the abbreviation AI has been readily recognizable. News outlets have recently carried headlines such as, “AI in your car can brake faster than you”, or “Police use AI to predict crime”, or similar flashy statements. But… Read More »

Creativity and Critical Thinking in the Age of Enterprise AI

January 16, 2018

What, if anything, should worry us about artificial intelligence today? Is it the worry that it will take over jobs around the world? Most definitely not. The fact of the matter is that what AI has gotten very good at solving for certain problem sets, however it still lacks overall knowledge of context to the… Read More »

Who cares if unsupervised machine learning is supervised learning in disguise?

January 11, 2018

Previously, we saw how unsupervised learning actually has built-in supervision, albeit hidden from the user. In this post we will see how supervised and unsupervised learning algorithms share more in common than the textbooks would suggest. As a matter of fact, both classes can use identical equations for creating mathematical models of the data, and… Read More »

Supervised learning in disguise: the truth about unsupervised learning

December 12, 2017

One of the first lessons you’ll receive in machine learning is that there are two broad categories: supervised and unsupervised learning. Supervised learning is usually explained as the one to which you provide the correct answers, training data, and the machine learns the patterns to apply to new data. Unsupervised learning is (apparently) where the… Read More »