Data Mining: Theory and Algorithms Tsinghua University (Yuan Bo)

This course completely covers all core technologies in the field of data mining, including data preprocessing, classification, clustering, regression, association, recommendation, ensemble learning, evolutionary computing, etc. Emphasizing on finding the best balance between the breadth, depth and interest of knowledge, the core ideas and key technologies of data mining, as well as some important knowledge points rarely covered in other related courses and textbooks, are described in vivid humor. This course is suitable for students from various majors and engineering and technical personnel who are interested in big data and data science. It does not pursue pure theoretical derivation, but organically combines theory with practice, allowing students to learn living knowledge, useful knowledge and real Your own knowledge, especially research methods and ways of thinking in the field of data analysis.

• Chapter 1：All ready to go (8 minutes and 23 seconds)

• Chapter 2：Learning without thinking means nothing (11 minutes and 4 seconds)

• Chapter 3：Unity of knowledge and action (22 minutes and 36 seconds)

• Chapter 4：From data to knowledge (14 minutes and 49 seconds)

• Chapter 5：Classification problem (18 minutes and 23 seconds)

• Chapter 6：Clustering and other data mining problems (12 minutes and 37 seconds)

• Chapter 7：Privacy protection and parallel computing (19 minutes and 49 seconds)

• Chapter 8：foggy (24 minutes and 5 seconds)

• Chapter 9：Related learning resources (3 minutes and 5 seconds)

• Chapter 10：Data cleaning (13 minutes and 10 seconds)

• Chapter 11：Outlier and duplicate data detection (13 minutes and 23 seconds)

• Chapter 12：Type conversion and sampling (17 minutes and 20 seconds)

• Chapter 13：Data description and visualization (15 minutes and 35 seconds)

• Chapter 14：Feature selection (12 minutes and 37 seconds)

• Chapter 15：Principal component analysis (24 minutes and 7 seconds)

• Chapter 16：Linear discriminant analysis_01 (12 minutes and 58 seconds)

• Chapter 17：Linear discriminant analysis_02 (16 minutes and 28 seconds)

• Chapter 18：Related learning resources (3 minutes and 22 seconds)

• Chapter 19：Bayesian Fantasy Journey (15 minutes and 56 seconds)

• Chapter 20：Simplicity is a virtue (26 minutes and 53 seconds)

• Chapter 21：Data, rules and trees (11 minutes and 48 seconds)

• Chapter 22：Knowledge about tree planting and afforestation (22 minutes and 57 seconds)

• Chapter 23：Related learning resources (2 minutes and 18 seconds)

• Chapter 24：Neurons, the Source of Wisdom (11 minutes and 46 seconds)

• Chapter 25：neurons that learn (12 minutes and 13 seconds)

• Chapter 26：from one to a group (10 minutes and 26 seconds)

• Chapter 27：Clear hierarchy, assigning responsibilities to everyone (19 minutes and 6 seconds)

• Chapter 28：Seeing the leopard in the tube, throwing bricks to attract good news (9 minutes and 55 seconds)

• Chapter 29：Related learning resources (3 minutes and 51 seconds)

• Chapter 30：maximum interval (13 minutes and 20 seconds)

• Chapter 31：Linear SVM (15 minutes and 57 seconds)

• Chapter 32：mathematician's trick (17 minutes and 59 seconds)

• Chapter 33：Salute to the true God (16 minutes and 50 seconds)

• Chapter 34：Related learning resources (5 minutes and 24 seconds)

• Chapter 35：unsupervised learning (12 minutes and 39 seconds)

• Chapter 36：K-Means (20 minutes and 25 seconds)

• Chapter 37：Expectation maximization method (19 minutes and 26 seconds)

• Chapter 38：density and layering (20 minutes and 26 seconds)

• Chapter 39：Item sets and rules (7 minutes and 25 seconds)

• Chapter 40：Support and confidence (8 minutes and 47 seconds)

• Chapter 41：Misunderstanding (5 minutes and 26 seconds)

• Chapter 42：Apriori algorithm (11 minutes and 13 seconds)

• Chapter 43：Case Analysis (14 minutes and 44 seconds)

• Chapter 44：sequence mode (10 minutes and 24 seconds)

• Chapter 45：Related learning resources (11 minutes and 12 seconds)

• Chapter 46：Recommended everywhere (10 minutes and 27 seconds)

• Chapter 47：implicit semantic analysis (17 minutes and 46 seconds)

• Chapter 48：PageRank Legend (10 minutes and 40 seconds)

• Chapter 49：Collaborative filtering (18 minutes and 13 seconds)

• Chapter 50：Tell you a real recommendation (15 minutes and 38 seconds)

• Chapter 51：Democratic Deliberation: Ensemble (9 minutes and 7 seconds)

• Chapter 52：Brainstorming: Bagging (17 minutes and 59 seconds)

• Chapter 53：Linked together: Boosting (19 minutes and 5 seconds)

• Chapter 54：The beauty of integration: AdaBoost (16 minutes and 34 seconds)

• Chapter 55：Carrying forward the past and opening up the future: RegionBoost (8 minutes and 27 seconds)

• Chapter 56：Human and Nature (14 minutes and 53 seconds)

• Chapter 57：Perfection (13 minutes and 52 seconds)

• Chapter 58：Towards evolution (11 minutes and 25 seconds)

• Chapter 59：A preliminary study on genetic algorithm (15 minutes and 32 seconds)

• Chapter 60：Advanced genetic algorithm (15 minutes and 47 seconds)

• Chapter 61：genetic programming (11 minutes and 1 seconds)

• Chapter 62：All things evolve (13 minutes and 16 seconds)

• Chapter 63：Related learning resources (6 minutes and 13 seconds)

• Chapter 64：The beauty of data (18 minutes and 48 seconds)

• Chapter 65：The southern redbud is also fragrant (8 minutes and 32 seconds)