What is the key difference between AI, machine learning and deep learning? What are some real life examples?

AI (Artificial Intelligence), machine learning, and deep learning are related concepts but differ in their scope and functionality. Here are the key differences along with real-life examples: Artificial Intelligence (AI):Scope: AI is a broad field of computer science that aims to create machines or systems capable of performing tasks that typically require human intelligence. It encompasses a wide range of techniques and approaches.Examples:Virtual personal assistants like Siri or Alexa that understand and respond to natural language.Self-driving cars that use AI to navigate and make decisions.Game-playing AI, like AlphaGo, which can defeat human champions in games like Go and Chess. Machine Learning (ML): Scope: Machine learning is a subset of AI that focuses on the development of algorithms and models that enable computers to learn and make predictions or decisions based on data. It's about teaching a machine how to improve its performance on a specific task without being explicitly programmed. Examples :Recommendation Systems: Services like Netflix and Amazon use ML to recommend movies or products based on user preferences .Image Classification: ML models can be trained to recognize objects in images, such as identifying animals in wildlife photo .Spam Email Filters: Email services use ML to filter out spam emails by learning from patterns in the data. Deep Learning: Scope: Deep learning is a subfield of machine learning that uses artificial neural networks, inspired by the structure of the human brain. It is particularly effective for tasks involving unstructured data, such as images, audio, and text. Examples :Image Recognition: Convolutional Neural Networks (CNNs) are used to identify objects in images, like Google Photos' image recognition .Speech Recognition: Deep learning powers voice assistants like Google Assistant and Apple's Siri .Language Translation: Services like Google Translate use deep learning models for accurate language translation. Key Takeaways: AI is the overarching field that aims to create intelligent machines. Machine learning is a subset of AI that focuses on teaching machines to learn from data. Deep learning is a subset of machine learning that uses neural networks for complex tasks, particularly with unstructured data. want to earn money by affliate marketing click link and start your affliate journey