Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
If someone's familiar with this, what would you say are the prerequisites?
This is taken from the book as it is:
Prerequisites This book assumes that you have some experience programming in Python and are familiar with the fundamentals of machine learning. The focus will be on building a strong intuition rather than deriving mathematical equations. As such, illustrations combined with hands-on examples will drive the examples and learning through this book. This book assumes no prior knowledge of popular deep learning frameworks such as PyTorch or TensorFlow nor any prior knowledge of generative modeling. If you are not familiar with Python, a great place to start is Learn Python, where you will find many tutorials on the basics of the language. To further ease the learning process, we made all the code available on Google Colab, a platform where you can run all of the code without the need to install anything locally.
I came in thinking it was a free ebook lol
Well it can be... «Архив Анны»
I guess it wouldn't sell shit if it used a language suitable for this type of work.
I mean, what happened to "use the right tool for the job"? There is Rust, C++, Julia, D, and certainly many more. Are they hard or what? Are they harder than mastering the math and algorithms that are relevant to an LLM? The code is actually pretty simple, certainly simpler than many "boring" apps.
Arguing that Rust, C++, Julia or D are a better "right tool for the job" than Python for a book that teaches people about LLMs is a bit of an eyebrow-raiser.
How so? Since when is Python a good language for numerical computation? What if the reader wants to try something that can ot be achieved by plumbing canned C++? They are out of luck I guess.
I assume you mean book's code shown in the Jypyter notebooks in the repository. (Which I think is both simple and messy.)