Jun 10, 2025 · 8 min read · Imagine training a machine learning model on millions of data points without your computer running out of memory. What if you could update your classifier in real-time as new data streams in, adapting instantly to changing patterns? This isn't scienc...
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Jan 21, 2025 · 21 min read · In my last three blog posts, we explained about how to reduce the wrong but high confidence of neural network, how to identify dead neurons, and The Kaiming initialization and batch normalization. The core of these three blog post is, the correct ini...
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Aug 15, 2024 · 4 min read · Stochastic Gradient Descent (SGD) is a cornerstone algorithm in the realm of machine learning. Its simplicity, efficiency, and effectiveness have made it a go-to choice for optimizing a wide range of models, from linear regression to deep neural netw...
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Jun 23, 2024 · 4 min read · In this article I'll be discussing about 3 things: Batch Gradient Descent Stochastic Gradient Descent Normal Equation Gradient Descent Gradient descent in machine learning is used to find the values of a function's parameters (coefficients), in ...
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