AI and Machine Learning – What is the difference?

AI and Machine Learning – What is the difference?

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People benefit from AI every day, right from Google Maps to Uber and even some delivery apps are all powered with artificial intelligence. However, there is significant confusion between the terms of artificial intelligence and machine learning, and most people wonder if they are the same thing. So, let’s clear it up, artificial intelligence (AI) and machine learning (ML) are two completely different things.

Artificial intelligence is a science and a way to build intelligent programs and machines that can creatively find solutions to problems that people cannot. Machine learning is a part of AI and provides an opportunity to automatically learn and improve from this kind of experience without being explicitly programmed. It consists of several algorithms that help to solve problems.

AI is divided into three categories:

Narrow or weak AI-

Narrow or weak AI can be explained by contrasting it against strong AI. Strong AI seeks to create artificial machines that have all the mental powers we have including a phenomenal consciousness. On the other hand, narrow AI seeks to create information-processing machines that have the complete mental ability of individuals.

General AI

General artificial intelligence certification can help in the future when machines become human-like. They will be able to make decisions, learn without human input, solve logical tasks, and have emotions.

Super Intelligence AI

This type of AI is way ahead of humans. It is smart, wise, and creative with excellent social skills. Its goal is to either make people’s lives better or destroy them all.

What is machine learning?

Machine learning is a subset of artificial intelligence that focuses on teaching computers how to learn without the need to be programmed for certain tasks. The key behind this is to create algorithms and make predictions on data. Machine learning courses online will teach you three components to educate the machine.

Datasets

Machine learning systems are specially trained to collect samples called datasets. These samples can include numbers, text, images, or other data and take a lot of time and effort to create.

Features

Features are an important piece of data that gives a viable solution to a task. They demonstrate to a machine what to pay attention to. For example, say you want to predict the price of a house, and how much the place costs based on its location, space, and more. This will help you find the cost based on the correlation between the price and the area the house is located in.

Algorithm

It is possible to solve the same task using a different algorithm. Depending on the algorithm, the accuracy and speed of the results can vary. Something you can get better performance and other time you need to combine various algorithm to achieve better results.

Summing It Up

Artificial Intelligence has several applications in the changing world of technology and uses a variety of methods to create something that can help human beings make their jobs and lives easier. AI has taken over several industries, companies, brands, and even military fields and is a job that is greatly in demand with a highly paid salary now and in the future. Taking up a course in AI will ensure that your future opportunities are bright. Machine Learning on the other hand is widely used in computations, pattern recognition, anomaly detection, and a range of commerce and businesses.

With the rise in big data, machine learning is used to solve problems in computation finance, credit scoring, algorithmic trading, computation biology (for detecting cancer,tumours, drug discovery, and DNA), energy production, automotive, aerospace, and image processing. It is also used in computer vision for face recognition, motion detection, and object detection as well as natural language processing. Taking up in course in machine learning can open up your possibilities greatly and gives you on-hands experience for when you are out in the field.

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Mike John

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