Big Data Processing Technology is a professional elective course for Computer Science and Technology majors (Big Data Direction) (Jingdong special) from high school to college and from college to university. With the current practical application of big data, cloud computing, deep learning and other content, big data processing technology has gradually become a professional compulsory course for computer majors. It contains many aspects such as data acquisition, feature engineering, data modeling, model prediction, data visualization, etc. It is a comprehensive discipline that integrates statistics, mathematical analysis, optimal control, computer algorithms up to program writing. Through the study of this course, learners will master data processing and the overall process, and be able to complete data modeling and prediction work for the data encountered in practice. Algorithmic models will be evaluated in the course using a lot of real data, and linear regression, Logistic/Softmax regression, BFGS proposed Newton's method, Decision Tree CART/Random Forest, SVM, kMeans, Density Clustering, Spectral Clustering SC, Labeling Passing Algorithm LPA, Collaborative Filtering, EM Algorithms/GMM, HMM, and so on, will be discussed in detail. In addition to discussing theoretical principles, the emphasis is on machine learning on the ground, and being able to implement or modify existing machine learning code on your own to be competent in practical problems encountered at work.