100-Days-Of-ML-Code

Why we included this project

100-Days-Of-ML-Code is a well-known learning track, and this is its Chinese translation, meant to be followed as a study plan rather than run as software. Each day combines a short infographic with a worked Jupyter notebook, covering data preprocessing, linear and logistic regression, k-NN, SVM, decision trees, random forests, and clustering. Readers who work in Chinese get translated explanations and code walkthroughs that are easier to follow than the original English material, and the infographics give a quick visual anchor before opening the notebooks. It works well as a day-by-day syllabus for building intuition about classic supervised and unsupervised methods before moving on to modern deep learning frameworks.