Today’s Question: What is Stochastic Gradient Descent? #interviewprep #machinelearning #datascience
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Today’s Question: What is Stochastic Gradient Descent? #interviewprep #machinelearning #datascience
👉 Learn the concept clearly in under 1 minutes, explained step-by-step with examples! 📚 About MLQs Café Welcome to MLQs Café — your go-to channel for mastering Python, Machine Learning, Data Science, Statistics, NLP, and AI research papers one question at a time. We simplify complex topics, decode research, and help you stay updated ...
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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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