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Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
Translated"Large Language Models" (《大语言模型》), authors: Zhao Xin, Li Junyi, Zhou Kun, Tang Tianyi, Wen Jirong
Source repo for the book
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
SICP PDF with Texinfo and LaTeX source
Source Code for Go In Action examples
In-depth understanding of Node.js: Core Ideas and Source Code Analysis
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Translated《御舆：解码 Agent Harness》(Yuyu, "Imperial Carriage: Decoding the Agent Harness"): 420,000 characters dissecting the Harness skeleton and nervous system of AI Agents — an in-depth analysis of the Claude Code architecture, 15 chapters from the conversation loop to building your own Agent Harness. Online reading website:
Translated📚 Go: Under The Hood | The Original Go Language (Go 语言原本) | https://golang.design/under-the-hood
Build a modern LLM from scratch. Every line commented. Explained like we are five.
Open source book dedicated to helping you to make the best possible sourdough bread at home.
The source code for the upcoming qml book
Sample Code of the App Architecture Book
XML sources of SICP and SICP JS, and support for generating Interactive SICP JS, PDF, e-book and comparison editions
An open-source full-length book on Docker
Learning Go Book in mmark
Sources codes for: Mastering Python for Finance, Second Edition
Code and data used to create the examples in "Evidence-based Software Engineering based on the publicly available data"
Book source for Controls Engineering in the FIRST Robotics Competition
Source code for the "Backbone.Marionette.js: A Gentle Introduction" book available at https://leanpub.com/marionette-gentle-introduction
This source code distribution is a companion to the AWS Lambda in Action book available from Manning Publications.
Online version of Bischl, B., Sonabend, R., Kotthoff, L., & Lang, M. (Eds.). (2024). "Applied Machine Learning Using mlr3 in R". CRC Press.
Evidence archive for Jesus of Nazareth: research dossier (PDF), New Testament, gnostic and extracanonical gospels, church fathers, ancient witnesses, Roman legal documents, archaeology, and all 238 cited references — searchable reader at https://sybil-solutions.github.io/all-historical-evidence-of-jesus-christ/