Ai-Learn

Ai-Learn is a Chinese-language guide to learning artificial intelligence from scratch, organized as a step-by-step learning roadmap. The repository was put together by a teacher who developed and refined roughly 200 hands-on examples over five years of in-person and online instruction. Each example uses real datasets, and the materials progress from the very basics to practical projects.

The suggested starting path covers Python programming, essential math (calculus, linear algebra, probability and statistics), and the Python libraries most commonly used in AI work: NumPy for matrix operations, Pandas for data handling, Matplotlib and Seaborn for visualization. The roadmap then moves through machine learning algorithms such as linear regression, logistic regression, decision trees, support vector machines, clustering, and boosting methods. Each algorithm section includes code, experiment comparisons, and working examples.

After the machine learning section, the roadmap covers deep learning using TensorFlow 2, PyTorch, Keras, and Caffe, followed by computer vision (with OpenCV) and natural language processing. Each area has project-level examples rather than toy code: predictive modeling on census income data, hotel recommendation systems, user churn prediction, Titanic survival classification, and others.

A free electronic version of the author companion book is available from the main repository page. The book was written over two years and revised more than ten times. Some supplementary materials such as datasets, slides, and code bundles are shared via Chinese cloud storage links in the README.

The repository is aimed at Chinese-speaking beginners who want to move from zero knowledge into practical AI work without wasted detours. The content is also useful for job-interview preparation, since many of the examples mirror common technical interview topics in the Chinese tech industry.