Importance of Accurate Predictions in Machine Learning
Machine Learning has emerged as a coveted branch of Artificial Intelligence in the recent past and large businesses have started to rely upon it. The reason behind this is its ability to make predictions about a future trend or an event. These predictions are made without much programming and input. This is the basic reason why the element of “prediction” is considered a crucial trait in machine learning.
Importance Of Accurate Predictions And Its Impact On Business
It is estimated that almost 75% of the businesses worldwide exist on the principle of forecast in their regular business functions. Out of these 75%, only 60% are equipped with the predictive and analytical capabilities. The major hindrance in the way of adoption of the analytical capabilities is the application of the correct set of analytical tools. The prediction function begins with the identification of storage of digital information and this information is vast. By implementation of the algorithms of Artificial Intelligence, businesses can optimise a whole new pattern of statistical application and enhance their predictive capability.
Type of Data Analysis
The basis of analytical activity is the vast amount of data. It is the foremost activity of the management to ensure that the application of analytics would fulfil the business expectations and business goals, which is appropriate for the environment of big data.
There are three types of analytics that are applied:
Descriptive Analytics – This is the basic form of analytics that aggregates the big data and provisions important insights of past events.
Predictive Analytics – The next level in the process of analytics is data reduction. There are various statistical modelling and machine learning techniques that are applied in this function. The function predicts future outcomes on basis of past data.
Prescriptive Analysis – The combination of business rules provides a new form of analytics, which is based on machine learning and computational modelling. This is done to recommend the best possible course for the business with an intended pre-specified outcome.
Neural Networks – Basis of Data Analysis
Neural networks refer to the hardware setups and the software applied in the system. This function is similar to the central nervous system of humans. It estimates the functions, which are dependent on huge amount of unknown inputs. The three aspects taken in consideration by Neural Networks are architecture, activity rule and learning rule.
Application Of Predictive Capabilities In Various Businesses
The function of predictive analytics works according to the nature, department and industry of the business. Some of the uses of Machine Learning based predictive analysis are:
E-Commerce – The use of Machine Learning can help the business to predict the fraudulent transactions and customer churn. It also helps the business to predict which customer would make the required click.
Marketing – The marketing is clubbed with Machine Learning to identify and acquire prospective customers with attributes that are similar to existing customers.
Customer Service – The analytics help in the customer service by conducting historical customer satisfaction surveys. These surveys help in correcting several activities such as total time, resolution of ticket, response delay etc.
Medical Diagnosis – Machine Learning is very useful in medical facilities to predict a particular illness. The prediction is based on the database of previous patients and the symptoms displayed by them in past.
Predictions paving way for business insights
Thus, machine learning uses various statistics and algorithms to find a relation between different sets of data. The likelihood of an event occurring in the future can be estimated thereby offering actionable insights to the business. These predictions can be a way to plan your business’ future, let it be for sales, purchase or defining customer behaviors.
Thus, prediction is a crucial component when it comes to defining strategies and taking actions based on the available data. Therefore implementing machine learning to get accurate predictions is a total win-win.