In the world of data science and artificial intelligence (AI), there is often a lot of confusion surrounding the terms “machine learning” (ML) and “deep learning” (DL). What exactly is the difference between these three terms? This blog post will attempt to explain the differences between AI, ML, and DL and explore an exciting data science certification opportunity. What is deep learning? Neural networks are machine learning algorithms modelled after the brain and can learn to patterns on their own. Deep learning is essentially a part of machine learning that uses artificial neural networks to recognise patterns in random data points. Deep learning algorithms can learn from unstructured and unlabeled data, making them more flexible than traditional machine learning algorithms. What is machine learning? Machine learning (ML) is a method of teaching pattern recognition from data without explicit external programming. It is a branch of artificial intelligence. It is based on the idea that systems can learn and adapt from data, thereby learning to identify patterns and make better decisions with minimal human intervention. The algorithms used in ML use models based on sample data, known as training data. This helps the systems to make more accurate predictions or recommendations about new data over time. For example, a machine learning algorithm might identify fraudulent credit card transactions or recommend products to customers based on their past purchases. Machine learning is often used interchangeably with artificial intelligence (AI) and deep learning, but there are important differences between these three fields. Differences between deep and machine learning Machine learning is a type of AI that teaches computers to learn from data and identify patterns. Deep learning is a subset of machine learning that uses algorithms to process highly abstract data. Deep learning is often used for image recognition and classification because it can automatically extract features from images; on the other hand, machine learning requires humans to specify what features to look for. What is AI and its 3 types? When we talk about Artificial Intelligence (AI), we are referring to the ability of a computer system to perform tasks that would typically require human intelligence. This can include understanding natural language, recognising objects, and making decisions. There are three main types of AI: - Artificial Narrow Intelligence: Only designed to perform particular tasks. It is considered a form of weak AI. - Artificial General Intelligence: A strong AI whose intelligence matches an average human's. - Artificial Super Intelligence: Another form of strong AI whose intelligence is superior to human intellect. Difference between AI, machine learning and deep learning There needs to be more clarity around the terms AI, machine learning, and deep learning. To clear things up, AI is a broad term that refers to anything that involves using computers to simulate or carry out human tasks. Machine learning is a subset of AI that focuses on training machines to learn from data and improve their predictions over time. Deep learning is a newer type of machine learning that uses neural networks to learn from data in a way that mimics the workings of the human brain. So what's the difference between these three terms? AI is the broadest term and includes any computer-based task requiring intelligence. This could be as simple as playing chess or as complex as driving a car. Machine learning is a type of AI that allows computers to learn from data and improve their predictions over time. Deep learning is a newer type of machine learning that uses neural networks to learn from data in a way that mimics the workings of the human brain. PG Certificate Programme in Data Science for Business Excellence and Innovation How do AI and machine learning play out in business? To understand this, you need to enrol in this data science certification, the PG Certificate Programme in Data Science for Business Excellence and Innovation, presented by IIM Nagpur. In this complex business world with ever-increasing data points, it is vital to understand the market effectively to make better decisions. With the aid of AI and machine learning (ML), this data science course in India plans to churn out competent data analysts who can become experts in their field. Conclusion When it comes to AI vs machine learning vs deep learning, there is a lot of overlap between these three terms. However, there are also some key distinctions that you should be aware of. In general, AI refers to the broader field of artificial intelligence, while machine learning and deep learning are two subfields within AI. By enrolling in the PG Certificate Programme in Data Science for Business Excellence and Innovation, you can learn all about the secrets of data science, as it is one of India's best data science courses.