• AI is the big idea of making machines smart.
• ML is a way to make machines learn and improve from experience.
• DL is a special kind of learning that makes machines even smarter by mimicking the human brain.

So, if AI is a brain, think of ML as a set of tools to teach the brain, and DL as a special technique for supercharging that brain. They all work together to make computers really clever and helpful!

Dear Doctor

"Artificial intelligence is the overarching system. Machine learning is a subset of AI. Deep learning is a subfield of machine learning, and neural networks make up the backbone of deep learning algorithms. It’s the number of node layers, or depth, of neural networks that distinguishes a single neural network from a deep learning algorithm, which must have more than three."

Artificial Intelligence (AI) is like making smart computers that can do things smart people usually do, such as solving problems and understanding language.

Machine Learning (ML) is a part of AI that teaches computers to learn on their own from information without being specifically told what to do.

Inside ML, there's something called Deep Learning (DL), which is a fancy way of saying computers use deep networks to figure out complicated patterns and details by themselves.

Together, these components form a hierarchy where AI is the overarching field, ML is a key subset within it, and DL is a specialized technique within ML, contributing to the overall advancement of intelligent systems. In other words, AI is a big idea, ML is a piece of that about learning, and DL is a smaller piece of ML that's good at figuring out tricky stuff all on its own.

AI encompasses the broader goal of creating intelligent machines, machine learning is a specific approach within AI that involves the development of algorithms capable of learning from data. Deep learning, on the other hand, is a subset of machine learning that relies on neural networks with multiple layers to achieve advanced pattern recognition and representation learning. In essence, AI is the overarching concept, machine learning is a subset of AI, and deep learning is a specialized form of machine learning.

You can find the simple answer in the attachment

AI (Artificial Intelligence), machine learning, and deep learning are related concepts, but they have distinct meanings and relationships with each other.

Here's a brief overview of each:

1. Artificial Intelligence (AI):

- AI is a broad field of computer science that aims to create machines or systems that can perform tasks that would typically require human intelligence.

- It encompasses a wide range of techniques and approaches, including rule-based systems, expert systems, knowledge representation, natural language processing, problem-solving, and more.

- AI can be categorized into two types: Narrow AI (or Weak AI), which is designed for a specific task, and General AI (or Strong AI), which would have the ability to perform any intellectual task that a human being can.

2. Machine Learning (ML):

- Machine learning is a subset of AI that focuses on the development of algorithms and statistical models that enable computers to improve their performance on a task over time without being explicitly programmed.

- ML involves the use of data to train models, and these models can make predictions or decisions based on new, unseen data.

- There are various types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.

3. Deep Learning (DL):

- Deep learning is a subfield of machine learning that specifically deals with neural networks, which are inspired by the structure and function of the human brain.

- Deep learning algorithms, known as neural networks, consist of multiple layers of interconnected nodes (neurons) that process and transform data.

- These networks can automatically learn hierarchical representations of data, extracting features at different levels of abstraction.

- Deep learning has been particularly successful in tasks such as image and speech recognition, natural language processing, and playing games.

As a result, AI is the broader field that encompasses efforts to create intelligent machines, while machine learning is a specific approach within AI that involves training models using data. Deep learning, in turn, is a subset of machine learning that focuses on neural networks with multiple layers (deep neural networks). Deep learning has gained prominence in recent years due to its success in handling large amounts of data and complex tasks.

Artificial intelligence

• AI allows a machine to simulate human intelligence to solve problems
• The goal is to develop an intelligent system that can perform complex tasks
• We build systems that can solve complex tasks like a human
• AI has a wide scope of applications
• AI uses technologies in a system so that it mimics human decision-making
• AI works with all types of data: structured, semi-structured, and unstructured
• AI systems use logic and decision trees to learn, reason, and self-correct

Machine learning

• ML allows a machine to learn autonomously from past data
• The goal is to build machines that can learn from data to increase the accuracy of the output
• We train machines with data to perform specific tasks and deliver accurate results
• Machine learning has a limited scope of applications
• ML uses self-learning algorithms to produce predictive models
• ML can only use structured and semi-structured data
• ML systems rely on statistical models to learn and can self-correct when provided with new data