Beyond Machine Learning: The Role of Mathematical Optimization
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Beyond Machine Learning: The Role of Mathematical Optimization
In episode 931 of the SuperDataScience podcast, Jerry Yurchisin confirms that, unlike statistics or machine learning, mathematical optimization can "provably find the optimal solution". He states this is the "big differentiator" and the reason it's called mathematical optimization is because "proofs are important". The technology provides a ...
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Insightforge | AI & Data Science on Instagram: "Stochastic Gradient Descent (SGD) is an optimization technique used to reduce a model’s loss and improve its performance. A good way to imagine it is like walking down a hill to reach the lowest point. The gradient tells you the slope and the direction to move downward. But instead of looking at the entire landscape (the full dataset), SGD looks at small random batches of data to estimate the slope at each step. Because it works with smaller sample
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Insightforge | AI & Data Science on Instagram: "Stochastic Gradient Descent (SGD) is an optimization technique used to reduce a model’s loss and improve its performance. A good way to imagine it is like walking down a hill to reach the lowest point. The gradient tells you the slope and the direction to move downward. But instead of looking at the entire landscape (the full dataset), SGD looks at small random batches of data to estimate the slope at each step. Because it works with smaller sample
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