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Aloha 👽, We learned a little about Large Language Models in our last series chapter, which brought us to the 3 types of LLMs (BERT, GPT, LLaMA). We’ll start with BERT. Let’s get right into it 🤖 It all started with Google Engineers yet again. Jacob ...

Comparison of Transformer Variants for Text Classification Text classification is one of the most widely used tasks in natural language processing (NLP), powering applications such as sentiment analysis, spam detection, topic labeling, intent reco...

Have you ever wondered how a computer knows that a cat is more like a dog than a car? To a machine, words are just strings of characters or arbitrary ID numbers. But in the world of Natural Language Processing, we’ve found a way to give words a home ...

Inthe rapidly evolving landscape of Natural Language Processing (NLP), Transformers have emerged as a foundational architecture that revolutionizes how we approach language understanding and generation. This comprehensive guide delves into the intric...

It was late evening.Riya sat in front of her laptop, staring at lines of text and code.Her model — a simple RNN — had just failed again. She sighed. “Why can’t you understand that ‘it’ refers to ‘the animal’ and not ‘the street’?” Her model didn’t ...

Imagine a child learning to read.At first, they look at every word on the page — slowly, carefully, sometimes losing the meaning of the whole sentence. But as they grow, they start to focus on the right words, understand tone, context, and emotion. T...
