Lets go through Paper of DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning – Day 80

Lets First Go Through its official paper of : DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning What Is DeepSeek-R1? DeepSeek-R1 is a new method for training large language models (LLMs) so they can solvetough reasoning problems (like math and coding challenges) more reliably. It starts with a base model(“DeepSeek-V3”) and then applies Reinforcement Learning (RL) in a way thatmakes the model teach itself to reason step by step, without relying on a huge amount of labeled examples. In simpler terms: They take an existing language model. They let it practice solving problems on its own, rewarding it when...

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98

Mathematical Explanation behind SGD Algorithm in Machine Learning _ day 5

In our previous blog post – on day 4 – we have talked about using the SGD algorithm for the MNIST dataset. But what is Stochastic Gradient Descent? Stochastic Gradient Descent (SGD) is an iterative method for optimizing an objective function that is written as a sum of differentiable functions. It’s a variant of the traditional gradient descent algorithm but with a twist: instead of computing the gradient of the whole dataset, it approximates the gradient using a single data point or a small batch of data points. This makes SGD much faster and more scalable, especially for large datasets....

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