@datascibykashi: If you’re learning data science, AI, or machine learning, this is one concept you must understand. LLMs like ChatGPT are trained on massive text data and learn patterns in language using something called a Transformer architecture. Here’s the simple breakdown: 1️⃣ Tokenization Text is broken into small pieces called tokens 2️⃣ Embeddings Each token is converted into numbers (vectors) so the model can understand it 3️⃣ Attention Mechanism The model looks at important words in context (Not all words matter equally) 4️⃣ Prediction It predicts the next word again and again That’s how sentences are generated 5️⃣ Training Trained on huge datasets using probability + optimization 💡 Simple idea: LLMs don’t “think” They predict the next best word based on patterns 💬 Comment Booster (VERY IMPORTANT) Which part confuses you most? A) Tokenization B) Attention C) Training D) How it generates answers 👇 Comment A, B, C, or D — I’ll explain it in the next video. 📌 Call to Action Save this if you’re learning Data Science & AI Follow for daily ML concepts. #creatorsearchinsights #datascience #ai #machinelearning #llm

Data Scientist | Kashi

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Monday 30 March 2026 06:21:32 GMT