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Grokking LLM: From Fundamentals to Advanced Techniques in Large Language Models
Anand V
1 episodes
6 days ago
Concepts like the evolution of language models, neural network architectures, and transformer mechanisms. It also explores popular LLMs like GPT-3 and BERT, delves into the intricacies of training LLMs, and discusses advanced techniques like prompt engineering, few-shot learning, and multimodal capabilities. The text concludes with practical applications across various industries, real-world implementations, and future trends for LLMs.
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Technology
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All content for Grokking LLM: From Fundamentals to Advanced Techniques in Large Language Models is the property of Anand V and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Concepts like the evolution of language models, neural network architectures, and transformer mechanisms. It also explores popular LLMs like GPT-3 and BERT, delves into the intricacies of training LLMs, and discusses advanced techniques like prompt engineering, few-shot learning, and multimodal capabilities. The text concludes with practical applications across various industries, real-world implementations, and future trends for LLMs.
Show more...
Technology
Episodes (1/1)
Grokking LLM: From Fundamentals to Advanced Techniques in Large Language Models
Grokking LLM: From Fundamentals to Advanced Techniques in Large Language Models

Concepts like the evolution of language models, neural network architectures, and transformer mechanisms. It also explores popular LLMs like GPT-3 and BERT, delves into the intricacies of training LLMs, and discusses advanced techniques like prompt engineering, few-shot learning, and multimodal capabilities. The text concludes with practical applications across various industries, real-world implementations, and future trends for LLMs.

Show more...
1 year ago
18 minutes 15 seconds

Grokking LLM: From Fundamentals to Advanced Techniques in Large Language Models
Concepts like the evolution of language models, neural network architectures, and transformer mechanisms. It also explores popular LLMs like GPT-3 and BERT, delves into the intricacies of training LLMs, and discusses advanced techniques like prompt engineering, few-shot learning, and multimodal capabilities. The text concludes with practical applications across various industries, real-world implementations, and future trends for LLMs.