Project Library

A project based on PyTorch, which uses artificial intelligence technology to quickly repair old photos. This project supports operations such as scratch detection, facial modification, and global restoration, helping users bring old photos back to life. This project demonstrates the potential and application of artificial intelligence in the field of image processing.

An AI quantitative trading platform, aiming to seek and explore the value of AI technology in the quantitative investment field. It contains a complete ML pipeline for data processing, model training, and backtesting, and covers the entire chain of quantitative investment: Alpha exploration, risk modeling, portfolio optimization, and transaction execution functions.

The author tries to predict the stock market based on machine learning.

LeetCode problem-solving template, which mainly records his experience in solving problems through various articles, columns, videos and other contents. It is for reference only

Java interview and learning guide, which covers most of the core knowledge that Java programmers need to master, including JVM, concurrency and multi-threading, common tool sets, data structures and algorithms, message queues, databases, etc.

算法理论基础知识应知应会

A developer in China has organized the LeetCode question classification and interview question answer analysis. It covers knowledge points such as linked lists, pointer traversal, string operations, stacks, recursion, dynamic programming, binary search trees, etc., and the solution code is implemented based on Java.

A big data interview question solution, mainly divided into three major chapters: Big Data Development Foundation, Framework Learning, and Practical Advanced, which includes high-frequency interview questions on technologies such as high concurrency, distributed, Hadoop, Spark, Flink, and Kafka.

Studying for a tech interview sucks. Here's an open source cheat sheet to help

Apps/CLIs/configs I use on macOS/iOS

A domestic developer has organized a set of notes on computer science learning, which includes technical classifications such as the principles of computer composition, data structures, computer networks, and operating systems. The content is organized very detailed, making it a very good reference for learning.

A developer has open-sourced the information technology competition courseware from 2013 to 2018 on GitHub. This courseware covers selected TopCoder problems, selected CodeChef problems, selected fun problems, network flow models and examples, NOIp graph theory, data structures and applications, etc.

The author is Josh Branchaud, a developer from Chicago. The purpose of creating this repository is to collect some fragmented programming knowledge and development skills he learned in his daily life. It includes classification of different technical fields such as Git, JavaScript, Linux, VSCode, Devops, Chrome, etc.

Google has open-sourced a document on engineering practices on GitHub. This document is the best practice accumulated by Google engineers over a long period of time. We hope that this document can help more developers complete code review work and provide standard references for project codes.

This is a repository suitable for beginners to advance from the basics. It solves the problems that interviewers and learners want to delve into C++ and how to get started with C++. In addition, this repository expands on more in-depth source code analysis, multi-threaded concurrency, etc., making it a relatively comprehensive repository for learning C++ from the basics to advanced improvement. Currently, it has 35,000 starts.