Nature

UNSUPERVISED LEARNING

 

 

 
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Unsupervised learning is used to draw inferences from data-sets consisting of input data without labelled responses. It involves training of computer using unstructured data and allowing the algorithm to act on that information without guidance.

The goal of unsupervised learning algorithms is to find patterns in any given unstructured dataset. It can be used for finding patterns in novels, articles, documents and processes..

 

TYPES OF UNSUPERVISED LEARNING

Unsupervised learning has two types. They are:.

  • Association: Association discovers the probability of the co-occurrence of items in a collection. It is all about finding association between items that frequently go together. Eg. If we purchase cup it will recommend coffee.                                      .
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  • Clustering : Clustering is the process of grouping similar entities together and understanding the attributes of different groups. There are many applications of grouping unlabelled data, for example, you can identify different types of work done by employees and group employees in teams with regards to the work they perform.

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Unsupervised machine learning offers great potential to disrupt the way business process automation is created. Currently, repetitive tasks and manual business processes cost 5 Trillion Dollars in lost productivity annually.

 

Tools such as Robotic Processes Automation (RPA) software's started in early 2000s, but only a fraction of business processes are being automated by these solutions. Only 9% of SMEs and 24% of large organisations have implemented RPAs tools. The main problems with these solutions is that they require technical knowledge, takes a long time to deploy (more than 3 months) and is not cost effective (costs more than 15,000 dollars per automation).

 

With the use of unsupervised and machine learning algorithms, the next generation of automation tools such as Zappy Analytics overcomes the barrier faced by RPA technology.

Zappy Analytics is an example of machine learning application which also uses unsupervised techniques to identify business processes and create automation for these processes.

 

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Zappy collects data on user actions, context and the application layout. Zappy Analytics uses the collected data and runs unsupervised learning algorithms to discover business processes. It presents analysis of the time spent on various business processes, identifies automatable processes and automatically generates automation's for these processes. With Zappy Analytics, you can identify the most time consuming and repetitive business processes performed in you organisation without the need of expensive consultants.

 

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Zappy overcomes the barrier presented by RPA technology and creates automation without any technical knowledge, in minutes and at a fraction of the cost.

 

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With Zappy Analytics organisations can save more than 70% of the time spent on business processes.