paul-lusztin-llm-resources

The internet is full of 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 about 𝗟𝗟𝗠𝘀 & 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀. But 𝗺𝗼𝘀𝘁 𝗼𝗳 𝗶𝘁 is 𝘁𝗿𝗮𝘀𝗵.

After 𝟲 𝗺𝗼𝗻𝘁𝗵𝘀 of 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴 𝗟𝗟𝗠𝘀 & 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀, here is a 𝗹𝗶𝘀𝘁 𝗼𝗳 𝗳𝗶𝗹𝘁𝗲𝗿𝗲𝗱 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 that I 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗹𝘆 𝘂𝘀𝗲 ↓

𝘉𝘭𝘰𝘨𝘴:

𝘈𝘳𝘵𝘪𝘤𝘭𝘦𝘴:

Patterns for Building LLM-based Systems & Products: https://lnkd.in/dNuzPw-m
RLHF: Reinforcement Learning from Human Feedback: https://lnkd.in/d96J6ERP
Illustrating Reinforcement Learning from Human Feedback (RLHF): https://lnkd.in/d8kPTSzp
Understanding Encoder And Decoder LLMs: https://lnkd.in/dnxhyuV8
Building LLM applications for production: https://lnkd.in/dWF4AhSz
Prompt Engineering: https://lnkd.in/d4gahQ7N
Transformers: https://lnkd.in/d5hchazs
Bidirectional Encoder Representations from Transformers (BERT): https://lnkd.in/dT9XbQbv
Multimodality and Large Multimodal Models (LMMs) by Chip Huyen: https://lnkd.in/daDs4Jiz

𝘝𝘪𝘥𝘦𝘰𝘴:

Word Embedding and Word2Vec, Clearly Explained!!! : https://lnkd.in/dcAmA4TW
Let’s build GPT: from scratch, in code, spelled out : https://lnkd.in/dCy-RBh9
Transformer Neural Networks, ChatGPT’s foundation, Clearly Explained!!! : https://lnkd.in/dveVjS2q
Large Language Models with Semantic Search : https://lnkd.in/dh6CtfZZ
Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!! : https://lnkd.in/d6CsWQy5

𝘊𝘰𝘥𝘦 𝘙𝘦𝘱𝘰𝘴𝘪𝘵𝘰𝘳𝘪𝘦𝘴:

𝘊𝘰𝘶𝘳𝘴𝘦𝘴:

…and hopefully, my Hands-on LLMs course will soon appear along them: ↳🔗 https://lnkd.in/dZgqtf8f

Let me know what you think of this list and have fun learning 🔥