#Tutorial

Explore a detailed guide to PyTorch with tutorials, video lessons, and suggested readings. Discover practical applications in NLP and computer vision using a variety of PyTorch repositories. This resource caters to learners of all levels, providing comprehensive support from foundational neural network concepts to advanced model training techniques.

Discover Stream's React Native SDK for diverse chat applications with detailed Expo and TypeScript components. Utilize examples like Slack and WhatsApp clones to streamline development. Designed for both hobbyists and large-scale projects, this SDK offers comprehensive documentation and free options for small teams, ensuring accessible implementation and seamless integration. Explore release notes for updates and consider contributing to a project supporting over a billion users.

Explore a detailed tutorial for integrating vector functionalities into relational database systems using C++ and Rust. Learn to implement features similar to pgvector on a modified BusTub system or add vector capabilities to the RisingLight system. Join the community on Discord for collaboration. The tutorial is shared under the MIT license, with some restrictions related to CMU-DB course content.

This repository provides concise tutorial codes for deep learning researchers to learn PyTorch efficiently, with models mostly under 30 lines of code. It presents a coherent learning trajectory from foundational topics like PyTorch basics, linear regression, to advanced subjects such as Generative Adversarial Networks and Neural Style Transfer. This guide serves as a practical supplement to the Official PyTorch Tutorial, offering vital resources for developing proficiency in PyTorch. The prerequisites include Python 2.7 or 3.5+ and PyTorch 0.4.0+.

Discover Next.js for a refined development journey featuring optimized Google Fonts and real-time editing. Seamlessly deploy applications with Vercel and harness technologies such as NextJS 14, Shadcn-ui, Prisma, and OpenAI. Tap into Next.js resources to enhance skills and connect with an active developer community, ideal for optimizing web app performance.

This repository provides a detailed collection of research papers on model-based reinforcement learning (MBRL), consistently updated with the latest developments. It includes papers from prestigious conferences such as NeurIPS and ICML and presents a taxonomy of MBRL algorithms categorized into 'Learn the Model' and 'Given the Model'. This resource is beneficial for studying foundational works as well as the latest innovations in the field, offering insights into various algorithmic strategies in model-based RL.

The LeeDL Tutorial, based on the acclaimed 2021 course from Professor Hung-yi Lee of Taiwan University, provides an engaging introduction to deep learning. By using anime-themed examples and a humorous teaching style, it breaks down complex theories. This tutorial offers detailed formula derivations, focusing on challenging concepts and expanding beyond earlier lectures to broaden understanding. Ideal for those interested in Chinese language explanations, it aids in developing deep learning intuition and exploring specialized areas.

Explore an insightful Korean tutorial offering free e-books, YouTube guides, and blog resources aimed at enhancing LangChain usage. Learn practical applications like local LLM hosting, task automation, and AI model implementation. Enjoy frequent updates and diverse tutorials specifically designed for Korean users, providing comprehensive insights into LangChain's functionalities. Suitable for developers and enthusiasts looking to expand their expertise in LangChain's capabilities.

The 'self-llm' project provides a step-by-step tutorial on using open-source large language models tailored for beginners in China. Focusing on Linux platforms, it covers environment setup, local deployment, and various fine-tuning techniques, including LoRA and ptuning, for models such as LLaMA and ChatGLM. This resource aims to assist students and researchers in understanding and applying these tools effectively in their studies and projects, while also welcoming community contributions to enrich this collaborative open-source initiative.

This repository contains detailed guides for replicating a diverse range of technologies from scratch. Step-by-step tutorials cater to varying levels of technical expertise, enhancing understanding of systems like 3D rendering, augmented reality, and blockchain. These resources simplify learning, making technical concepts accessible. Users can explore projects across categories, including bots, command-line tools, databases, and complex systems like operating systems and web browsers. This collection is excellent for gaining practical experience and understanding the core functionalities of modern technologies.