mikoto10032/deeplearning

This repository is a curated collection of learning materials for deep learning, the branch of artificial intelligence (AI) that powers things like image recognition, language models, and recommendation systems. It is primarily aimed at Chinese-speaking learners, as the vast majority of the content is in Chinese. The collection is organized as a structured roadmap, starting from mathematical foundations (like linear algebra and probability), moving through machine learning basics, and then into deep learning topics. It links to lecture notes, video courses from universities and online platforms, textbooks in PDF form, and external GitHub repositories covering areas like computer vision, natural language processing (understanding and generating text), and reinforcement learning (training AI through reward signals). The repo also includes practical sections on engineering skills for AI roles, including Kaggle competition strategies, algorithm interview preparation, and how to use deep learning frameworks. The content is not code written by the author, it is a curated index pointing to resources elsewhere. It is built as a Jupyter Notebook project and covers topics including convolutional neural networks (CNNs, used for images), generative adversarial networks (GANs, used for image synthesis), and graph convolutional networks (GCNs, used for structured data like social graphs). Someone exploring AI or preparing for a machine learning job in a Chinese-language environment would find this a useful starting guide.