Introduction

Machine Learning algorithm learns from experience E concerning some kind of task T and performance measurement P. If its task T in that performance is measured by P, enhance with experience E. Let’s consider an example Of a Machine Learning algorithm that is also used to play chess. Then, experience E is playing many chess games, task T is playing chess with many players, and the performance measure P is the probability that the algorithm will win.

You can also read: What are the best cyber security books for beginners?

Top 3 Applications of machine learning

Most respected companies or many websites offer the opportunity to chat with a customer support agent. Hence, after asking any query by the customer, the answer doesn’t need to be provided by humans only; occasionally, the answers are provided by the chatbot, which withdraws the information from the website and gives the answer to customers. Online chatbots are replacing customer support agents along the customer journey, transforming the way we guess about customer engagement over websites and social media platforms. Now they are better and understand the queries quickly and faster and also provide a good result by giving appropriate results, and the uses of machine learning only do it.

You can also read: Top 30 Companies in India to Work For in Data Science and Machine Learning

Conclusion

Machine Learning is also extremely important in healthcare diagnosis as it can be used to diagnose various problems in the medical field. Machine Learning is also utilized in oncology to train algorithms that can identify cancerous tissue at the microscopic level with the same exactness as trained physicians. In this way, you can see that the applications of Machine Learning are limitless. If anything, they are only increasing, and Machine Learning may one day be used in almost all fields of study!