The Advantages and Disadvantages of Machine Learning

What is Machine Learning (ML)?

Machine learning is a counterpart of artificial intelligence (AI), it brings the ability for technological systems to improve and learn automatically from past experience without being programmed manually to do tasks. In other words, the focus of machine learning is on developing programs on computers that can access data and learn from it automatically without the assistance or intervention of humans. Machine learning is either supervised or unsupervised.

Supervised machine learning applies to the information learnt from the past to new data utilising labelled classifications to predict events of the future. While unsupervised machine learning is applied when the information utilised to train data is not labelled or classified.

What are the advantages of Machine Learning?

Rapid Analysis Prediction and Processing

Machine Learning enables the possibility for individuals to make appropriate decisions at the right time. For example, Machine Learning will optimize the best offers for customers of the business, the customers will be able to see the right offers at any period of time, and without the business investing time to manually make the right ads visible for their customers.

Interpret Past Customer Behaviours

Machine Learning will allow businesses to analyze the data related to past behaviours of customers and interpret those patterns. Thus, based on the new data retrieved, businesses will be able make better predictions of customer behaviours.

Simplifies Time-Intensive Data Entry

The major issues that are faced by businesses are inaccuracy and duplication of data. These issues can be addressed by algorithms of machine learning and predictive modelling. Machine learning allows computer programs to execute time intensive data entry tasks, which leaves the skilled resources free to focus on other duties that add value to the business.

 What are the disadvantages of Machine Learning?

Acquisition of data

Machine Learning requires huge sets of data to train on, these data sets tend be biased, and does not meet the right quality. There are also moments where businesses have wait for some time for the generation of the new data.

Time and resources

Machine Learning requires enough time to allow the algorithms to develop and learn to accomplish their tasks with a reasonable amount of relevancy and accuracy. Machine Learning also requires huge number of resources to function, this suggests a need for more computational power for businesses.

Interpretation

The ability to interpret results that are generated by the Machine Learning algorithms accurately is lacking which is a major issue. Businesses must carefully choose the algorithms to use for their purposes. The ability to interpret the results of machine learning algorithms is also affected by the lack of skills towards machine learning in businesses.

High error susceptibility

High amounts of data is used by Machine Learning algorithms and also, the algorithms are utilised and tested. So a huge change in the algorithms or data  sets may lead to experiencing many errors.

Conclusion

In this fast paced life, businesses need to manage all their work within a given time in this case with Machine Learning their systems makes a few decisions automatically to keep it updated with the resources that really necessary. Machine learning with the assistance of artificial intelligence solutions and other cognitive technologies brings new opportunities and efficiency for business.

Machine Learning allows businesses to discover new patterns and trends effortlessly from diverse and large data sets. Many businesses nowadays have automated analysis when interpreting the interactions of the business, which were initially done by humans manually. This encourages businesses to deliver new, differentiated or personalized products and services. Thus, by thinking of Machine Learning as a strategic plan is seen a wise decision. Deploying Machine Learning algorithms carries certain business risks. Therefore, itis better for businesses to look at investment decisions with utmost consideration and care.