@kaanberke
Software Engineer
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Nov 6, 2023 · 2 min read · Probability distributions are a key component of many deep learning systems. By understanding the advantages and disadvantages of using probability distributions, we can build more effective models. In this post, I'll explore when probability distrib...
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Oct 22, 2023 · 3 min read · In the world of deep learning, linearity and non-linearity are fundamental concepts that allow neural networks to learn and perform complex tasks. Understanding how they work is key to building effective deep learning models. What is Linearity? In ma...
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Oct 20, 2023 · 4 min read · Let's start by answering What is a Logarithm? Imagine you're baking cookies and the recipe calls for 8 chocolate chips. You want to know how many times you'll need to double a single chocolate chip to end up with 8 chips total. You start with 1 chip....
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Sep 23, 2023 · 2 min read · Batch normalization has become a key technique for training deep neural networks. But what exactly does it do and why is it so important? In this post, we’ll explain batch normalization using an analogy, walk through the technical details, and cover ...
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Sep 17, 2023 · 2 min read · Google Brain researchers have discovered a new optimization algorithm for training deep neural networks called Lion that outperforms the popular Adam optimizer on a variety of computer vision and natural language processing tasks. In a paper publishe...
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