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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

Description:

Explore the inner workings of large language models and ChatGPT in this comprehensive 36-minute video tutorial on prompt engineering. Delve into the Transformer architecture, text embedding, and self-attention mechanisms. Learn about key deep learning methods, compare DALL-E and ChatGPT, and gain hands-on experience with Python code for multi-head self-attention and LLM parameter counting. Master the art of generating effective keywords and prompts to enhance your understanding of artificial intelligence and natural language processing technologies.

Prompt Engineering - Understanding Large Language Models with ChatGPT

Prodramp

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#Computer Science #Artificial Intelligence #Natural Language Processing (NLP) #Prompt Engineering #Deep Learning #LLM (Large Language Model) #ChatGPT #Machine Learning #Text Embedding #Transformer Architecture #Self-Attention