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Deep Learning & Machine Learning

<From Scratch: Building and Learning LLMs> Commentary Lecture

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

(4.8) 21 reviews

527 learners

Level Basic

Course period Unlimited

  • haesunpark
PyTorch
PyTorch
gpt-2
gpt-2
transformer
transformer
LLM
LLM
Fine-Tuning
Fine-Tuning
PyTorch
PyTorch
gpt-2
gpt-2
transformer
transformer
LLM
LLM
Fine-Tuning
Fine-Tuning

"LLM & AI with PyTorch" Book Publication and Event Announcement

Hello. I'm Haesun Park.

It's been a while, but I'm happy to announce the publication of a new book.

<AI and Machine Learning for Coders> author Laurence Moroney's new book <Llama 2 and Beyond: A Guide to LLMs with PyTorch> has been published!

The previous book focused on deep learning applications using the TensorFlow ecosystem. This book uses PyTorch instead of TensorFlow and focuses on generative AI, such as LLMs and diffusion models. It is now available at online and offline bookstores! The e-book has also been released! ๐Ÿ™‚

I have created a short video summarizing what's new compared to the previous edition. Share this video on your social media, and five winners will be selected to receive a copy of from Hanbit Media! You must register on the Google Form after sharing it on social media. Please refer to the instructions below!

  • Video URL to share: https://youtu.be/vEwY31kDtl4

  • Please register the SNS URL where your shared content can be viewed in the Google Form (https://forms.gle/9CMP37YMugpkA8G96).

  • If you cannot register the URL address, please upload a screenshot instead.

  • Event Period: 3/5 (Thu) ~ 3/13 (Fri)

  • Winner Announcement: 3/16 (Mon) (Winners will be contacted individually)

The books will be sent directly by Hanbit Media.

We look forward to your participation.

Thank you!

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