Machine Learning Usage in Different Industries

1. Machine Learning Usage in Different Industries Machine learning (ML) has become one of the most prominent buzzwords in industry circles. And that is not without reasons. The growing popularity of ML in business has arisen due to its slew of benefits. But, before examining the ML benefits, let us look at the use cases. There are many uses of ML, such as: Recommendations You must have seen recommendations on popular streaming platforms, such as Spotify and Netflix. And these recommendations are outcomes of ML algorithms. The algorithms analyze the songs you have listened to or the videos you have watched. In addition, the algorithms also analyze other data–about songs, shows and consumer habits – to suggest the content you may enjoy. Fraud Detection ML algorithms are essential in detecting fraud in banks and other financial institutions. The algorithms can detect transactions outside parameters, such as purchase amount and user location. After the detection, the algorithms alert the user when such unusual activity occurs. Search Engine Results When you search on Google, ML algorithms analyze your behavior to deliver useful results. For example, if you continuously search for a page that was not highly ranked on the initial results page, Google puts that page higher for your future searches. Chatbots Chatbots are typical examples of ML algorithms at work. The bots work as dedicated customer care executives working round-the-clock to resolve customer queries. For example, when you post a query to a chatbot, the ML algorithm answers it through automated responses.

2. Spam Filters ML algorithms protect your inbox from unwanted emails. In addition, the algorithms act as a spam filter by analyzing the characters in subject lines, body content and return addresses. Customer Retention Businesses need to retain their customers because of the stiff competition. And ML algorithms can help companies retain their customers by analyzing the changing behaviour of the existing customers. Let us illustrate an example to make things clear. Suppose one of your customers has stopped using your credit card due to a better offer from a competitor. ML algorithms will send better offers to the customer to retain him. Sentiment Analysis ML algorithms have played a key role in analyzing customer sentiments. The algorithms use natural language processing to discover the underlying sentiments in social media posts. So, sentiment analysis can help businesses to understand how customers feel about their brand or product. Real Estate Valuation The real estate industry seems to be one of the biggest winners from using ML algorithms, which have made estimating real estate values a quick and dependable affair. The algorithms analyze the available data on the features and the sales of houses in a locality to estimate the best value of real estate properties. Learning Platforms Nowadays, there has been a steady rise in the usage of educational apps by students. ML algorithms analyze student data to fix the course duration at the student’s convenience.

3. Medical Image Processing ML algorithms are a great boon to medical companies. The algorithms can identify hidden diseases in X-rays to warn the doctors in advance. So, doctors can prescribe the corresponding treatments before the condition aggravates. The Associated Challenge In addition to several benefits resulting in increasing the efficiency and productivity of businesses, ML comes with some challenges. The need to work with large amounts of business data will bring challenges. But, you need to address the challenges to maintain your competitiveness. One of the ways to handle the associated challenges is to outsource the ML application task to an ML company. Nowadays, you will find many machine learning solution companies. Such companies have competent professionals to handle the associated challenges and derive the best results. Conclusion ML can transform your business, helping you to take it to the next level. So, you should start implementing ML if you have not yet implemented the algorithms.