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Types of Machine Learning

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  Machine learning is a field of artificial intelligence that focuses on creating computer systems that can learn from data and make predictions or take actions based on that data. There are several different types of machine learning techniques, each with its own advantages and applications. Here are three of the most common types of machine learning: Supervised Learning: Supervised learning is a type of machine learning where the computer is trained on labeled data, meaning that each example in the dataset is labeled with the correct output. For example, if the task is to classify images of cats and dogs, each image in the dataset would be labeled as either a cat or a dog. The computer uses this labeled data to learn how to make accurate predictions on new, unlabeled data. Some common algorithms used in supervised learning include decision trees, random forests, and neural networks. Unsupervised Learning: Unsupervised learning is a type of machine learning where the computer is t...
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What is Machine Learning ?

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  Machine learning is a branch of artificial intelligence that focuses on creating computer programs that can learn from data and improve their performance over time. It has become increasingly popular in recent years due to its ability to provide valuable insights and predictions based on vast amounts of data. In machine learning, computers are trained to recognize patterns in data, which enables them to make predictions or take actions based on that data. There are two main types of machine learning: supervised learning and unsupervised learning. Supervised learning involves training a machine learning model on labeled data, while unsupervised learning involves training a model on unlabeled data. Machine learning has a wide range of applications in various fields, including healthcare, finance, marketing, and more. For example, in healthcare, machine learning can be used to analyze patient data and make predictions about their health outcomes. In finance, machine learning can be ...
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