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  2. Learning AI and ML involves the following key points1234:
    • Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on using data and algorithms to enable AI to learn and improve its accuracy.
    • ML algorithms are trained on data to produce adaptable models that can perform complex tasks.
    • Deep learning, a subset of ML, uses neural networks with multiple layers for complex tasks.
    • ML enables systems to learn autonomously from experience rather than explicit programming.
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    Machine learning (ML) is a branch of artificial intelligence (AI) and computer science that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.
    www.ibm.com/topics/machine-learning
    Machine learning (ML) is a subfield of AI that uses algorithms trained on data to produce adaptable models that can perform a variety of complex tasks. Deep learning is a subset of machine learning that uses several layers within neural networks to do some of the most complex ML tasks without any human intervention.
    www.coursera.org/articles/machine-learning-vs-ai
    Machine learning is a subset of AI, which enables systems to learn autonomously from experience rather than explicit programming. Models are trained with large data sets, using algorithms to analyze data and improve task performance and decision-making.
    pg-p.ctme.caltech.edu/blog/ai-ml/deep-learning-vs-…
    Machine learning is a subset of artificial intelligence focused on developing algorithms with the ability to learn without explicitly being programmed. Deep learning is a subset of machine learning. It is responsible for many of the awe-inspiring news stories about AI in the news (e.g., self-driving cars, ChatGPT).
    www.datacamp.com/blog/how-to-learn-ai
     
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