AI & ML - A QUICK OVERVIEW FOR BEGINNERS

Artificial Intelligence?

• AI is based on the idea that human intelligence can be defined and mimicked by machines to execute tasks. ?
• From simple to complex,?artificial intelligence is focused on accomplishing all kinds of tasks. ?
• AI goals include learning, reasoning, and perception, but the benchmarks for AI are always changing and developing as technology develops. ?
• Some technology that was once revolutionary AI is now considered basic computer functions, and that trend of technology growth is likely to continue.??
• Data managers?or data scientists help utilize AI and develop ways to keep the data secure and available for us to use. AI research involves helping data-driven machines learn how to take new data as part of their learning problem and solution process.?
• Artificial intelligence is the larger, broader term for how we utilize machines and help them accomplish tasks. Machine learning is a current application of artificial intelligence that we utilize in our day-to-day lives. Machine-learning systems are a smaller facet of the larger AI systems.??

Example?

Chatbots, Online shopping, Streaming services, Healthcare technology, Factory and warehouse systems, educational tools are some examples.

Machine Learning?

• Machine learning is an application of AI that is based around the idea that we can give machines data, and allow them to learn for themselves.?
• Machine learning utilizes neural networks to take data, and use algorithms to solve pieces of the problem, and produce an output. ?
• Machine learning encompasses one small part of the larger AI system—machine learning focuses on a specific way that computers can learn and adapt based on what they know.?
• Deep learning?is a facet of machine learning, simply meaning that the neural networks used are larger to parse bigger data sets or more complex problems. Deep learning utilizes the same neural networks and machine learning models, but on a much larger scale. This deep learning is important for larger data sets—deep learning is the way that we can get more information, parsing more data than has ever been possible before.?
• Machine learning and deep learning focus on ensuring a program can continue to learn and develop based on what outputs it has come up with before. There are three different kinds of intelligence systems involved in machine learning models and machine learning algorithms.?
• Supervised learning focuses on giving an input and an output, and helping the machine get there. Supervised learning helps an intelligent machine understand how their algorithms should get to the final output. Supervised learning is more hands-on that other types of intelligent machine learning.?

Example?

Smart home assistants, social media, Translation services, Autonomous vehicles?