Upload docs.jsonl

docs.jsonl

@@ -1,5 +1,300 @@
-{"source": "Wikipedia", "text": "Python is a high-level, interpreted programming language known for its readability and broad standard library."}
-{"source": "Wikipedia", "text": "The theory of relativity encompasses two interrelated theories by Albert Einstein: special relativity and general relativity."}
-{"source": "Stanford CS229 Notes", "text": "Gradient descent is an optimization algorithm used to minimize the cost function by iteratively moving in the direction of steepest descent."}
-{"source": "Khan Academy", "text": "The derivative represents the rate of change of a function with respect to a variable."}
-{"source": "DeepLearning.ai", "text": "Convolutional neural networks are a class of deep neural networks primarily used to analyze visual imagery."}
+{"source": "Wikipedia", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Wikipedia", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "Neural networks are inspired by the human brain."}
+{"source": "Wikipedia", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "DeepLearning.ai", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Neural networks are inspired by the human brain."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Coursera", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Stanford CS229 Notes", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Stanford CS229 Notes", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Khan Academy", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Wikipedia", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Stanford CS229 Notes", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "DeepLearning.ai", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "Coursera", "text": "Neural networks are inspired by the human brain."}
+{"source": "Coursera", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "A confusion matrix summarizes classification performance."}
+{"source": "DeepLearning.ai", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Khan Academy", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "DeepLearning.ai", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "DeepLearning.ai", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Stanford CS229 Notes", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "DeepLearning.ai", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Coursera", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Relativity explains how time and space are linked."}
+{"source": "DeepLearning.ai", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Khan Academy", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "DeepLearning.ai", "text": "A confusion matrix summarizes classification performance."}
+{"source": "DeepLearning.ai", "text": "Python is a versatile programming language."}
+{"source": "Coursera", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Wikipedia", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "DeepLearning.ai", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "Neural networks are inspired by the human brain."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Neural networks are inspired by the human brain."}
+{"source": "Khan Academy", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Coursera", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Stanford CS229 Notes", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Stanford CS229 Notes", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Coursera", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "Coursera", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Khan Academy", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Stanford CS229 Notes", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "DeepLearning.ai", "text": "Relativity explains how time and space are linked."}
+{"source": "Stanford CS229 Notes", "text": "Relativity explains how time and space are linked."}
+{"source": "Khan Academy", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "DeepLearning.ai", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
+{"source": "Khan Academy", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Coursera", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Stanford CS229 Notes", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Coursera", "text": "Relativity explains how time and space are linked."}
+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
+{"source": "DeepLearning.ai", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Python is a versatile programming language."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Relativity explains how time and space are linked."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "Khan Academy", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Wikipedia", "text": "Python is a versatile programming language."}
+{"source": "Stanford CS229 Notes", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "Relativity explains how time and space are linked."}
+{"source": "Coursera", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Coursera", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "Neural networks are inspired by the human brain."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Coursera", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "Stanford CS229 Notes", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Coursera", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Coursera", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "Relativity explains how time and space are linked."}
+{"source": "Khan Academy", "text": "Neural networks are inspired by the human brain."}
+{"source": "DeepLearning.ai", "text": "Relativity explains how time and space are linked."}
+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Coursera", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Wikipedia", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "Relativity explains how time and space are linked."}
+{"source": "Wikipedia", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "DeepLearning.ai", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Stanford CS229 Notes", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Wikipedia", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Khan Academy", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Coursera", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "Coursera", "text": "Neural networks are inspired by the human brain."}
+{"source": "Khan Academy", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Relativity explains how time and space are linked."}
+{"source": "Coursera", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Stanford CS229 Notes", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Wikipedia", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "DeepLearning.ai", "text": "Relativity explains how time and space are linked."}
+{"source": "Khan Academy", "text": "Python is a versatile programming language."}
+{"source": "Wikipedia", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "DeepLearning.ai", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Relativity explains how time and space are linked."}
+{"source": "Wikipedia", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Coursera", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Coursera", "text": "Relativity explains how time and space are linked."}
+{"source": "DeepLearning.ai", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "The derivative is a fundamental concept in calculus."}
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+{"source": "Khan Academy", "text": "Activation functions introduce non-linearity into neural networks."}
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+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Khan Academy", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Stanford CS229 Notes", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "A confusion matrix summarizes classification performance."}
+{"source": "DeepLearning.ai", "text": "Python is a versatile programming language."}
+{"source": "DeepLearning.ai", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Khan Academy", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Khan Academy", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Coursera", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "DeepLearning.ai", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Coursera", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Wikipedia", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "DeepLearning.ai", "text": "Python is a versatile programming language."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Stanford CS229 Notes", "text": "The derivative is a fundamental concept in calculus."}
+{"source": "DeepLearning.ai", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Coursera", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Khan Academy", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "DeepLearning.ai", "text": "Overfitting occurs when a model performs well on training data but poorly on unseen data."}
+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Relativity explains how time and space are linked."}
+{"source": "Stanford CS229 Notes", "text": "Gradient descent is an essential optimization algorithm."}
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+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
+{"source": "Stanford CS229 Notes", "text": "Neural networks are inspired by the human brain."}
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+{"source": "Khan Academy", "text": "Matrix multiplication is a key operation in linear algebra."}
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+{"source": "Coursera", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Khan Academy", "text": "A confusion matrix summarizes classification performance."}
+{"source": "Coursera", "text": "Neural networks are inspired by the human brain."}
+{"source": "DeepLearning.ai", "text": "Activation functions introduce non-linearity into neural networks."}
+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "DeepLearning.ai", "text": "Matrix multiplication is a key operation in linear algebra."}
+{"source": "Stanford CS229 Notes", "text": "A confusion matrix summarizes classification performance."}
+{"source": "DeepLearning.ai", "text": "Gradient descent is an essential optimization algorithm."}
+{"source": "Stanford CS229 Notes", "text": "Relativity explains how time and space are linked."}
+{"source": "Coursera", "text": "Activation functions introduce non-linearity into neural networks."}
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+{"source": "Wikipedia", "text": "Neural networks are inspired by the human brain."}
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+{"source": "Coursera", "text": "Matrix multiplication is a key operation in linear algebra."}
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+{"source": "Stanford CS229 Notes", "text": "Backpropagation is used to compute gradients in deep learning models."}
+{"source": "Wikipedia", "text": "A confusion matrix summarizes classification performance."}
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+{"source": "Khan Academy", "text": "Gradient descent is an essential optimization algorithm."}
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+{"source": "Khan Academy", "text": "Relativity explains how time and space are linked."}
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+{"source": "Wikipedia", "text": "A confusion matrix summarizes classification performance."}
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+{"source": "Coursera", "text": "Relativity explains how time and space are linked."}
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