文件名称：MA28CP-Intro-to-Machine-Learning
文件大小：52.64MB
文件格式：ZIP
更新时间：2024-06-11 09:29:36
JupyterNotebook
MA28CP-机器学习入门
【文件预览】：
MA28CP-Intro-to-Machine-Learning-master
----L11_intro to model selection()
--------L11_intro to model selection.pdf(789KB)
--------L11_pipelines and gridsearch.ipynb(17KB)
----L05b_distance measures()
--------L05b_distance metrics.pdf(509KB)
--------L05b_euclidean.ipynb(7KB)
--------L05b_chebyshev.ipynb(3KB)
--------L05b_mahalanobis.ipynb(8KB)
--------L05b_seuclidean.ipynb(15KB)
--------L05b_cityblock.ipynb(4KB)
--------L05b_distance measures.pdf(1.17MB)
----L04_sci-python()
--------L04_scipython_notes.pdf(675KB)
----L01_intro()
--------L01_ml-overview_slides.pdf(9.21MB)
--------L01_ml-overview_notes.pdf(1.32MB)
----L13_ensemble methods()
--------07-ensembles__notes.pdf(2MB)
--------L13_ensemble methods.pdf(3.45MB)
--------code()
----LICENSE(1KB)
----L05c_nearest centroid classifier()
--------L05c_nearest centroid scratch.ipynb(21KB)
--------L05c_nearest centroid sklearn.ipynb(23KB)
----L08_linear and quadratic discriminant analysis()
--------tharwat2016.pdf(928KB)
--------L08_Linear and quadratic discriminant analysis.pdf(1.81MB)
--------aic729.pdf(880KB)
--------1906.02590.pdf(1.75MB)
----L03_python()
--------L03-python_notes.pdf(256KB)
----L05_preprocessing-and-sklearn()
--------L05_preprocessing-and-sklearn_slides.pdf(2.73MB)
--------L05_pandas-cheat-sheet.pdf(549KB)
--------code()
----L09_principal component analysis()
--------PCA_anOverview.pdf(2.2MB)
--------pca.py(507B)
--------PrincipalComponentAnalysis-ATutorial (1).pdf(1.95MB)
--------principal_components.pdf(117KB)
----L10_LDA x PCA()
--------L10_linear_discriminant_analysis.ipynb(332KB)
--------L10_LDA x PCA.pdf(1.11MB)
----L15_model evaluation 2()
--------code()
--------09-eval2-ci__slides.pdf(4.58MB)
--------09-eval2-ci__notes.pdf(869KB)
--------L15_model evaluation 2.pdf(2.53MB)
----.gitignore(31B)
----L12_decision trees()
--------L12_decision trees.pdf(4.47MB)
--------code()
--------L12_decision trees notes.pdf(1.34MB)
----L00_presentation()
--------L00_presentation_slides.pdf(33KB)
----README.md(35B)
----L14_model evaluation()
--------code()
--------08-model-eval-1-intro__notes.pdf(1.08MB)
--------L14_model evaluation.pdf(3.31MB)
----L07_naive bayes()
--------L06_naive bayes.pdf(1.81MB)
----L02_knn()
--------02-knn_notes.pdf(1.18MB)
--------code()
--------02-knn_slides.pdf(1.88MB)
----L06_gaussian distribuition()
--------L06_1D descritive.ipynb(68KB)
--------L06_1D gaussian.ipynb(109KB)
--------Marks.csv(5KB)
--------L06_Gaussian (normal) distribution.pdf(2MB)
--------L06_ND descritive.ipynb(17KB)
--------L06_ND gaussian.ipynb(629KB)