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Prompt Engineering - Understanding Large Language Models with ChatGPT

Prodramp via YouTube

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Overview

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This course explains the technology behind ChatGPT and large language models, covering transformer architecture, text embeddings, encoder-decoder structure, self-attention, and key deep learning methods. It includes PyTorch code for multi-head self-attention and compares ChatGPT with DALL-E.

Syllabus

Content Intro
ChatGPT
Transformer architecture
Keywords Generation
Text embedding
Encoder and Decoder
Self attention
Multi-head self attention
PyTorch Code Multi-head self attention
Scaled Dot Product Attention
Key deep learning methods
Large language models
LLM Parameter Count Python Code
DALL-E large language model
Key Differences DALL-E & ChatGPT
List all Prompts
ChatGPT Session Summary

Taught by

Prodramp

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