Vector Embeddings and Tokens скачать в хорошем качестве

Vector Embeddings and Tokens

Iss video mein hum embeddings ka concept bahut hi simple aur easy Hinglish mein samjhenge. Hum dekhenge 👇 ▶️ What are Embeddings? Embeddings ka basic meaning samjhenge — data ko numbers (vectors) mein convert karna taaki machine samajh sake. ▶️ Simple Real-Life Examples: Laptop, cat, dog jaise simple examples se embeddings ka concept feel karenge. ▶️ Text → Tokens → Embeddings: Samjhenge kaise text ko pehle tokenize kiya jaata hai aur phir har token ka embedding vector generate hota hai. ▶️ OpenAI Tokenization (Practical View): Practically dekhenge kaise OpenAI tokenization work karta hai ek simple input ko tokens mein kaise break kiya jaata hai. ▶️ Embedding Dimensions: Vector embeddings ki dimensions kya hoti hain aur kyun different models ki embeddings different length ki hoti hain. ▶️ OpenAI Embeddings API Example: Last mein hum OpenAI embeddings API ko REST client se hit karke ek real embedding response dekhenge. Video ke end tak aapko embeddings, vector dimensions, tokenization aur OpenAI embeddings API ka complete flow clear ho jaayega — bilkul beginner-friendly way mein.