Introduction to Machine Learning
“Machine learning” is the concept where it gives the computer systems the ability to learn and act on its own without being programmed for specific action or outcome.
Knowingly or unknowingly we use machine learning application in our day-to-day life, may it be mobile games, social media portals, google maps, or in any shopping portals.
This is the era where the whole world is driven by the computer systems and it has reached to an extent of understanding human emotions right from love to hatred or stress to happiness.
Why Machine Learning?
Machine Learning(ML) is the field of artificial intelligence where it involves giving data to the computer and drawing out certain results without being specifically programmed. It has the dynamic ability to alter the result based on the new data and ML mainly helps in predictive analysis.
Applications of Machine Learning in business
Most of the businesses have implemented machine learning in their business to know their customers and their potential in driving the revenue. Thanks to artificial intelligence for its “predictive modelling” algorithm for its ability to forecast the trends and behaviour of the customer by which there is much impact on the strategy which they make for their targeted customers.
To name few applications of MI in business-
1). Prediction of customer Lifetime value
Consumer lifetime value(CLV) is the concept in the business wherein it involves predicting the future profits from an associated customer. In other words, it can be said that total monetary value gained by the relationship with the customer through his entire lifetime.
Normally in any business 80% of the business is derived from the 20% of the customers. Some customers really matter for leveraging the business and most importantly identifying such customers is significantly valuable. It helps in forecasting the budget allocation and thus helps in optimising advertising campaigns and strategic spend on customers.
2). Segmentation of the customers
In this connected world, people expect that experience where they are satisfied and delighted with product or service. If a brand fails to do this it loses one. Marketers must be microscopic in their segmentation strategy to win the competition.
Personalized communication is the most successful way of doing business. It gives the brand a different array. With Machine learning, there is a scope for identifying the customer’s pattern of buying, like, dislikes, history of purchase etc which can help in deriving the result for engaging them personally.
3). Recommendation Engines
We all know that man is a social animal. He always likes to have a company in all the little things he does, may it be shopping or to travel. He needs an advice, suggestion and a reason a buy. Over the period, shopping trends and pattern is changing and that friends, colleague has been slowly replacing with the intelligent recommendations engines which suggests buyer the products which is based on their interest, buying pattern etc. Engines use Artificial Intelligence to draw the best results for every customer.
4). Fraud Detection
Frauds are unavoidable and it is present almost in every country. Preventing fraud is always better than investing in the process of detecting the fraud. Businesses now have the solution for it and they can easily avoid the transaction frauds with the aid of machine learning.
5). Trading and Financial
ML and AI have been also used in some areas of financial trading in making strategies, suggesting the investment decisions to the clients, stock price prediction etc. Implementing AI reduces time, cost and prominently it reduces the intensive manual work. Many big brands are utilizing AI in the areas like image recognition for extracting important data points in the legal documents.
6). Machine learning In Healthcare
Currently, the healthcare industry in India is worth about 160 billion dollars. It’s been driven by the technology and in near future, the manual works in this sector will be replaced by the machines right from the billing to diagnosis of the patient health.
Adoption of ML & AI is transforming the healthcare sector drastically and it’s taking to the new areas which is so effective that the machine can diagnose the possible heart attacks in much advance and patient can take possible action immediately
7). Data security
In the current connected world, cybersecurity is highly demanding and plays a crucial role in the business. Intelligent machines now smarter and can protect the data more efficiently than ever. It can detect network intrusion, phishing and other security tools. ML can be used for developing authentication systems, implementation of protocols and related tools keeping the various systems safe.
Above is the statistics which portrays the adoption level of ML/AI. More than 50% business has not yet adopted these technologies in their business. But gradually the numbers changes soon as “Technology is the key to success”, and impact which makes in the business process is tremendous.
By- Vinay Prasad, SourceEdge Software Technologies
SOURCEEDGE SOFTWARE TECHNOLOGIES PVT LTD