What is AI in machine learning ?

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AI (Artificial Intelligence) is a broad term that refers to the ability of a machine or computer to learn from its environment and experiences, and to use that knowledge to complete tasks that would ordinarily require human intelligence. AI in machine learning is the use of algorithms to identify patterns in data and make predictions or decisions based on those patterns. Machine learning algorithms can be supervised or unsupervised, and can be used in fields such as image recognition, natural language processing, predictive analytics, and robotics.

 

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What is Artificial Intelligence (AI) in Machine Learning?

Artificial Intelligence (AI) is a branch of computer science that focuses on creating intelligent machines that can think and act like humans. AI is used in a wide range of applications, from robotics to natural language processing. AI is also used in machine learning, which is a type of artificial intelligence that allows machines to learn from data and improve their performance over time.

Machine Learning is a subfield of AI that focuses on developing algorithms that can learn from data and improve their performance without being explicitly programmed. Machine learning algorithms use data to make predictions and decisions. They can be used for tasks such as predicting the stock market, recognizing images, and recognizing speech.

AI in Machine Learning is the application of artificial intelligence techniques to machine learning algorithms. AI techniques can be used to improve the performance of machine learning algorithms by providing them with more data, better features, and better algorithms. AI techniques can also be used to automate the process of training and testing machine learning algorithms. AI techniques can also be used to create more robust and accurate models that can be used in a variety of applications.