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Hands-On Large Language Models
- relyks 2y agoIf someone's familiar with this, what would you say are the prerequisites?
- saqrais 2y agoThis 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.
- samchon 2y agoI came in thinking it was a free ebook lol
- triyambakam 2y agoWell it can be... «Архив Анны»
- d_tr 2y agoI guess it wouldn't sell shit if it used a language suitable for this type of work.
- d_tr 2y agoI 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.
- antononcube 2y agoI assume you mean book's code shown in the Jypyter notebooks in the repository. (Which I think is both simple and messy.)
- simonw 2y agoArguing 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.
- d_tr 2y agoHow so? Since when is Python a good language for numerical computation? What if the reader wants to try something that cannot be achieved by plumbing canned C++? They are out of luck I guess. Good job teaching the sloppy semantics of a scripting language for numerics I guess.
- simonw 2y ago"Since when is Python a good language for numerical computation?" 30 years. Numeric came out in 1995, then evolved into NumPy in 2005. https://en.m.wikipedia.org/wiki/NumPy https://en.m.wikipedia.org/wiki/NumPy Almost every AI researcher and AI lab does most of their research work in Python.
- d_tr 2y agoI know all of these facts. Doesn't mean it is how it is for the right reasons, and even if it is, it does not imply that it is a good way to teach.
- qwertox 2y agoOfficial code repo for the O'Reilly Book - "Hands-On Large Language Models" No text of the book in there.
- curtisszmania 2y ago[dead]