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Machine learning involves training models to make predictions or take actions based on input data. Algorithms in Python include decision trees, random forests, gradient boosting, KNN, SVM, neural networks, and many more. These algorithms can be implemented using popular Python libraries such as scikit-learn, TensorFlow, and PyTorch.

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Machine-Learning-in-python

Machine learning involves training models to make predictions or take actions based on input data. Algorithms in Python include decision trees, random forests, gradient boosting, KNN, SVM, neural networks, and many more. These algorithms can be implemented using popular Python libraries such as scikit-learn, TensorFlow, and PyTorch. https://youtube.com/playlist?list=PLKnIA16_Rmvbr7zKYQuBfsVkjoLcJgxHH

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Machine learning involves training models to make predictions or take actions based on input data. Algorithms in Python include decision trees, random forests, gradient boosting, KNN, SVM, neural networks, and many more. These algorithms can be implemented using popular Python libraries such as scikit-learn, TensorFlow, and PyTorch.

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