Machine learning has emerged as a popular offshoot of artificial intelligence (AI), and is being widely used in several industries. Machine learning can be defined as computer systems’ ability to learn and adapt from their experiences. While it has gained widespread popularity only in recent years, machine learning has been in use in numerous real-life scenarios for quite a while. Some of the real-life applications of machine learning include AI personal assistants and chatbots, email autoresponders, personal finance and banking, healthcare and medical diagnosis, self-driving cars, and commute and transportation. In the healthcare sector, machine learning models can analyze patient data to assist in precise disease diagnosis and prognosis, while in the finance sector, it can predict market trends and assist in building diversified investment portfolios. Machine learning is expected to continue playing a vital role in various industries by enabling automation and enhancing user experiences.
Tesla, a prominent player in the automobile industry, has incorporated machine learning in their modern cars, which capable of self-learning object recognition and detection. Other ride-hailing apps like Uber have utilized machine learning to make features like ride pricing, pickup locations, optimal routes, and estimated arrival times automated. Google Maps also utilizes machine learning algorithms to provide intelligent navigation and predict traffic. In the banking and finance sector, machine learning algorithms can detect fraudulent activities in transactions by leveraging image and text recognition techniques.
NVIDIA is a popular company mentioned in this article for providing AI hardware for self-driving cars, which incorporates unsupervised machine learning models to enable self-learning object recognition and detection capabilities.
Siri, Alexa, and Google Assistant are all examples of personal assistants and chatbots that utilize machine learning algorithms.
The article provides a comprehensive overview of machine learning, with examples from across several industries, showcasing how the technology has transformed various aspects of our everyday lives.
