文件名称：DATA-SCIENCE-NOTES:PYTHON，机器学习，SQL，Tableau
文件大小：276.82MB
文件格式：ZIP
更新时间：2024-05-19 17:32:41
数据科学注释 PYTHON，机器学习，SQL，Tableau 我正在共享一些工业专家的帮助下自己写的笔记。 希望这对数据科学社区的人们非常有帮助。 编写的注释非常简单，也易于理解和实施。 非常感谢您参考我的笔记。
【文件预览】：
DATA-SCIENCE-NOTES-main
----35. STEPS FOR RANDOM SAMPLING WITH AN EXAMPLE.pdf(1.65MB)
----33. MISSING VALUES TREATMENT.pdf(4.63MB)
----59. HIERARCHICAL CLUSTERING, K-MEANS++, PCA.pdf(10.38MB)
----48. LOGISTIC REGRESSION ASSUMPTIONS, KNN ALGORITHM, HYPERPARAMETER TUNING.pdf(8.07MB)
----50. DECISION TREE.pdf(5.01MB)
----21. PLOTTING WITH PANDAS.pdf(3.8MB)
----44. STEPS OF ALGORITHMS & EVALUATION METRICES.pdf(5.87MB)
----47. HANDLING UNDERFITTING & OVERFITTING, MISCLASSIFICATION & MAXIMUM LIKELIHOOD ESTIMATION.pdf(7.08MB)
----37. HYPOTHESIS TESTING WITH AN EXAMPLE.pdf(9.42MB)
----9.2 CLASS & LOCAL, GLOBAL VARIABLES IN OOPS CONCEPT.pdf(4.06MB)
----30. UNIFORM RANDOM VARIABLE.pdf(1.22MB)
----38. EXAMPLES OF HYPOTHESIS TESTING.pdf(2.51MB)
----41. LINEAR ALGEBRA.pdf(2.73MB)
----34. INFERENTIAL STATISTICS.pdf(4.42MB)
----18. WORKING WITH .CSV.pdf(3.82MB)
----26. EXAMPLES OF REGEX.pdf(7.91MB)
----8. OOPS CONCEPT.pdf(3.44MB)
----7. FUNCTIONS.pdf(3.76MB)
----54. IMPORTANT CONCEPTS IN MACHINE LEARNING.pdf(6.63MB)
----52. SUPPORT VECTOR MACHINE.pdf(7.93MB)
----4. DATATYPES .pdf(5.16MB)
----1. PYTHON INTRODUCTION.pdf(2.13MB)
----9.1 HTML.pdf(3.42MB)
----42. LINEAR REGRESSION.pdf(3.72MB)
----3. OPERATORS.pdf(3.62MB)
----46. ADVANTAGES & DISADVANTAGES OF LINEAR REGRESSION, LOGISTIC REGRESSION.pdf(6.53MB)
----36. USING T-SCORE.pdf(2.02MB)
----31. NORMAL DISTRIBUTION & ITS PROPERTIES, DATA ANALYTICS FRAMEWORKS.pdf(6.26MB)
----45. ASSUMPTIONS OF LINEAR REGRESSION.pdf(2.97MB)
----28. PROBABILITY.pdf(2.65MB)
----README.md(350B)
----57. COMPONENTS OF NLP.pdf(3.45MB)
----29. RANDOM VARIABLE.pdf(2.87MB)
----5. PROPERTIES OF DATATYPES.pdf(5.38MB)
----58. K-MEANS CLUSTERING.pdf(3.77MB)
----13. JINJA TEMPLATING.pdf(807KB)
----40. MACHINE LEARNING & LINEAR ALGEBRA INTRODUCTION .pdf(9.32MB)
----24. PLOTLY.pdf(3.82MB)
----2. BASICS OF PYTHON, IDENTIFIERS, RESERVED WORDS, DATATYPES.pdf(4.17MB)
----53. PERFORMANCE METRICES.pdf(3.8MB)
----12. CREATING PYTHON CODE IN HTML.pdf(1.17MB)
----22. UNI & BIVARIATE ANALYSIS.pdf(4.92MB)
----10. ACCESSING METHODS OF CLASS.pdf(3.72MB)
----25. REGULAR EXPRESSIONS.pdf(3.94MB)
----43. GRADIENT DESCENT & OPTIMIZATION OF LINEAR REGRESSION.pdf(4.88MB)
----19. PANDAS DATAFRAME.pdf(4.39MB)
----23. PLOTTING WITH SEABORN.pdf(7.25MB)
----16. NUMPY BROADCASTING & PANDAS INTRODUCTION.pdf(2.33MB)
----55. GRID & RANDOMIZED SEARCH CV.pdf(4.01MB)
----32. Q-Q PLOT, PARETO DISTRIBUTION, BOX-COX PLOT, PLOTTING UNIFORM & NORMAL DISTRIBUTION.pdf(7.4MB)
----49. KNN REGRESSION.pdf(1.24MB)
----14. NUMPY.pdf(2.74MB)
----6. DECISION CONTROL STATEMENTS.pdf(3.08MB)
----15. NUMPY RANDOM NUMBERS GENERATION.pdf(10.18MB)
----20. MERGING & GROUPBY.pdf(3.26MB)
----27. WEB SCRAPING.pdf(1.72MB)
----60. VERSION CONTROL SYSTEM.pdf(1.69MB)
----39. CHI-SQUARE TEST.pdf(1.7MB)
----17. PANDAS.pdf(7.83MB)
----56. NATURAL LANGUAGE PROCESSING.pdf(3.97MB)
----11. FOUR PILLARS OF OOPS CONCEPT.pdf(7.93MB)
----51. GINI INDEX, RANDOM FOREST, BAGGING.pdf(8.31MB)