Machine Learning uses algorithms and understands data to improve. Artificial intelligence and machine learning are the biggest technological development in today’s corporate world. These technologies are shaping the world with their ability to deliver innovative answers to complex problems. There are various types of machine-learning algorithms such as linear regression and support vector machines. Machine learning is a part of artificial intelligence in which ML uses data and algorithms to improve themselves. Machine learning gives identical results for different inputs and provides a range of possible results. It allows them to handle complicated tasks.
Businesses utilizing machine learning know that industry development needs constant invention. Companies are improving their businesses on the consumer level and in business activity. Companies usually use machine learning to change business for the better. It is easier to gather data from the consumer than through AI algorithms. AI has created machine learning. Companies constantly engage in a contest with competitors to assure consumers. Artificial intelligence and machine learning are the answers for businesses to earn an edge over competitors. Most machines are established to do one task at a time while through machine learning businesses use AI for digital modification, digital systems are continuously adjusting to the surrounding conditions. Machine learning is suitable for companies delivering cost-effective solutions to issues that earlier needed plenty of resources. Using AI, you can automate several tasks from the following behavior to sending mass emails.
1) Curated Timelines on Twitter - Twitter is moving towards an algorithmic feed and of late Twitter holds everyone's mind on social media platforms because of their decision-making to change the way people are tagged in replies. Twitter shows you tweets chronologically and these changes are done with the help of machine learning technology. Twitter’s AI assesses each tweet in real-time and gives scores to them. Eventually, Algorithms show tweets that are likely to get the most engagement and reach. Machine learning makes decisions based on particular choices which result in curated feeds.
2) Image Classification - look at a picture and decide what it comprises but AI algorithms are created to analyze pictures. Image classification is the process by which algorithms are taught to analyze pictures and algorithms have advanced to be greater than humans. Some companies are using image classification to control undesirable content from coming into the feed. Companies utilize image classification answers to improve efficiency with the help of machine learning. Companies also use it to identify customer verification. Image classification is becoming popular due to its ability to drastically change existing systems.
3) Customer Support - Retaining customers is the most important for an e-commerce company that requires delivering customer support effectively and on time. So, most companies use machine learning to improve the customer support experience. Machine learning builds a system that evaluates customer support queries and transfers negative responses to the top. Chatbots give support without the help of a human operator to respond. Chatbots can increase consumer satisfaction by responding faster. Customers also prefer to interact with chatbots over humans.
4) Personalization - Machine learning improves the experience and personalizes its recommendations for customers. Netflix uses this feature very effectively by viewing viewers' history with similar interests and details about particular shows and movies then recommending content according to that analysis. Using AI for recommendations is a very familiar technique that is used by other streaming companies also to grow sales. Netflix uses AI for various purposes such as auto-generation and personalizing thumbnails and optimizing streaming quality by analyzing bandwidth. It helps to keep viewers engaged and decreases the chances of canceling their subscriptions. Netflix even takes AI help to determine audience size.
5) Improving E-commerce -have struggled to overpower the disconnect between offline shopping and online shopping. When online shopping started, companies thought offline shopping had come to an end but many e-commerce platforms still needed to earn more profit. Machine learning can help e-commerce platforms to improve the experience for customers. Machine learning provides a more pleasing experience for customers by analyzing individual behavior and movements. Nowadays, Companies trying to make casual browsing more rewarding than offline shopping and window shopping.
6) Deep Learning - Companies have been using machine learning for a very long time. Companies use deep learning to recommend videos to viewers which are based on a massive analysis of data. The analysis also shows people tend to like and watch videos that similar people have watched. YouTube recommends videos by analyzing the viewing history of users and the viewing history of users with similar interests. Since 2008, YouTube has been building this technology but before then, recommendations were based on what had the most views. According to YouTube, They use big neural networks.
7) Healthcare- IBM uses a technology called Watson to test and experiment with self-learning behavioral standards. Watson has been installed in various hospitals and medical centers where it proved its skill for completing highly accurate treatment suggestions with such precision. Watson also shows notable potential where it could be used as an assistant to doctors as well as in hospitals. IBM is also offering its Watson machine learning technology on a license basis to other companies. This is one of the biggest examples of an Artificial intelligence application being shared with other companies in this manner.
8) Text Parsing - Machine learning is used to understand a human-generated text by training the language and grammar of Artificial intelligence, so it is possible to process considerable data in less time. This process is called text parsing which comes under natural language processing. Text parsing is useful for both analyzing existing data and gathering new data either from user-generated content or competitors. This technology helps the company that deals with a big amount of text data. Text parsing has the potential to replace many low-skilled employees because AI can process considerable amounts of text at a very fast rate, and companies benefit from text parsing. Text parsing allows companies to use a fast search engine for simple tasks and a more complicated algorithm for advanced conditions. It reduces the requirement for hiring low-skill labor to parse text.
9) Smooth User experience -Dating apps have changed the game by using machine learning to develop a user experience smoothly by helping in making perfect matches. Dating apps use an algorithm that looks at a combination of various factors such as your age, location, and interests to find perfect matches for you. It also analyzes your conversation with other users to give you perfect matches. Another company called Yelp is also using machine learning to improve user experience. Yelp is trying to improve how it handles image processing by implementing its picture classification technology. Yelp’s machine learning algorithms help the company’s staff to collect, organize, and label images more efficiently.
10) Manufacturing - Intel uses machine learning for chip manufacturing. Intel chips power your computer’s core processor which could be the reason for navigating different tabs at the same time. Intel's Nervana chips are prepared for data center servers and utilize machine learning for data processing. Machine learning also helps in Nervana chips transferring 2.4 terabytes per second with very low latency.