Machine Learning vs. Artificial Intelligence — Main Differences!

Machine Learning vs. Artificial Intelligence — Main Differences!

Machine learning and artificial intelligence are two terms that people use interchangeably, but they are quite different even after sharing certain similarities. Both of these terminologies are related to computer science and have changed our lives in more than one way. Nowadays, people benefit from artificial intelligence every day in terms of booking a cab, accessing Google maps and finding the best music recommendation, etc. ML, on the other hand, helps sort out a huge pile of data accurately. What other differences are there? Keep scrolling to know more.

Machine Learning

ML is a branch of AI and can be defined as a study of algorithms that help computers or machines to improve through data and experience, without any human help. ML is a way to achieve AI with the results that programmers derive by applying effective ML methods. The best machine learning bootcamps focus on working on small to large datasets by comparing and examining the patterns and trends to explore nuances.

For instance, if you feed an algorithm a list of your favorite songs along with the kind of genres you enjoy more, the machine learning model will generate a recommender model based on the data to give you a playlist you would like more in the future. This is the same execution that platforms like Netflix, Spotify, etc. use to derive better consumer-centric results. This is known as supervised learning. Unsupervised learning is the kind of ML algorithms that do not have output categories. Reinforcement learning, on the other hand, focuses on studying the data at hand in the best possible manner to maximize the outcomes.

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Artificial Intelligence

When discussing about machine learning vs. artificial intelligence, the latter has a huge scope and a variety of applications. It is a science of making computers work in a way that people originally thought needed human intelligence while training these systems to do better. Here the focus is more on succeeding than on accuracy and to simulate natural intelligence to get a task done. These days, AI signifies Human-machine interactions with mediums like Google Home, Alexa, Siri, with ML-powered platforms like YouTube, Netflix, and Amazon. ML and AI help make our lives more productive.

Key takeaways

ML is defined as the acquisition of skills while increasing accuracy. The outcome is not as significant as doing the task with precision because ML is all about studying the data accurately. It is as simple as the machines taking data and then studying it to derive results. Programmers create self-learning algorithms and train machines to learn on their own.

AI can be defined as the ability of machines to gain knowledge on its own with the help of data provided. The focus is on achieving success, and not accuracy. The focus is to imitate human intelligence amongst machines to solve complex tasks.

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Sign up for Bootcamp Training

SynergisticIT is one of the best machine learning bootcamps that can help you gain expertise in the field of data science and analytics. The curriculum is devised to cover both theoretical and practical aspects to prepare candidates for a successful professional career. You can study basics along with advanced technologies to get an absolute learning experience. So fast track your ML or AI career by beginning your training at the right place and gain real-world exposure.