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ML vs DL vs AI
Machine learning (ML), deep learning (DL), and artificial intelligence (AI) are all terms used to describe a variety of technologies that are used to enable machines to learn, act, and make decisions on their own. ML is a subset of AI, which is focused on using algorithms to learn from data, while DL is a subset of ML that uses multiple layers of artificial neurons to process data. AI is a broader term that describes any kind of technology that enables machines to make decisions on their own or to act without explicit instructions.
ML and DL are used to create algorithms that can learn from data and make decisions based on that data. ML algorithms are used to detect patterns in data, while DL algorithms are used to improve the accuracy of these patterns by using multiple layers of artificial neurons. AI is a broader term that can include both ML and DL algorithms, as well as other technologies such as natural language processing (NLP) and computer vision.
Machine learning (ML), deep learning (DL), and artificial intelligence (AI) are all terms used to describe a variety of technologies that are used to enable machines to learn, act, and make decisions on their own. ML is a subset of AI, which is focused on using algorithms to learn from data, while DL is a subset of ML that uses multiple layers of artificial neurons to process data. AI is a broader term that describes any kind of technology that enables machines to make decisions on their own or to act without explicit instructions.
ML and DL are used to create algorithms that can learn from data and make decisions based on that data. ML algorithms are used to detect patterns in data, while DL algorithms are used to improve the accuracy of these patterns by using multiple layers of artificial neurons. AI is a broader term that can include both ML and DL algorithms, as well as other technologies such as natural language processing (NLP) and computer vision.