文件名称：Data-Science-Projects:数据科学项目汇编
文件大小：47.08MB
文件格式：ZIP
更新时间：2024-06-16 06:38:42
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机器学习存储库 机器学习案例研究
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Data-Science-Projects-master
----Unsupervised Day1.html(543KB)
----Big Sales Mart - Lasso & Ridge Regression (2).ipynb(571KB)
----Confidence Interval & Central Limit Theorem.ipynb(52KB)
----House Price Prediction using Lasso and Ridge.ipynb(747KB)
----Anova with Calculations and Dataset.ipynb(93KB)
----.gitignore(500B)
----Binomial & Poisson Probability Distribution.ipynb(22KB)
----KNN - Network Intrusion Case Study.html(343KB)
----Unsupervised Day 2.html(594KB)
----Anova and Chi Square Test.ipynb(97KB)
----Big Sales Mart.html(854KB)
----01-Support Vector Machines with Python.html(317KB)
----Sampling_and_Confidence_Intervals.ipynb(12KB)
----Predicting Food Delivery Time - Machine Hack Case Study.ipynb(107KB)
----Understanding Anova & Chi Square Test in Titanic.ipynb(60KB)
----Hierarchical Clustering.html(440KB)
----SharlaGelfandProject.pdf(1.07MB)
----SMOTE - Credit Card Fraud Detection.ipynb(29KB)
----K Means Clustering (1).ipynb(134KB)
----Network_Intrusion.csv(2.74MB)
----Linear Regression - Tips Dataset.ipynb(100KB)
----NUMPY - 100 EXERCISES.pdf(260KB)
----Titanic Final Script.html(831KB)
----GIT Guide.pdf(4.16MB)
----Linear Regression in Python.html(1.15MB)
----Ensemble Models Diabetes Dataset.html(315KB)
----Introduction to GGPLOT.html(695KB)
----Machine Learning Projects in Python.pdf(1.99MB)
----Probability Basic Binomial Poisson and Continuous.ipynb(162KB)
----Day 02 - Ensemble.ipynb(215KB)
----Ensemble Methods Part 02.html(2.78MB)
----Hypothesis Testing in Python.html(295KB)
----Big Sales Mart Statistics.ipynb(117KB)
----Kaggle Competition - Predicting House Prices Using PCA.ipynb(162KB)
----Normal_Distribution_&_Z_Test_Test_One_Sample_&_Independent.ipynb(30KB)
----Logistics Regression - Loan Dataset.html(327KB)
----Linear Regression ML Day 02.html(316KB)
----Big Sales Mart - EDA & Outlier Removal - GBM RMSE 1105.ipynb(554KB)
----Introduction to Categorical Data Analysis Alan Agresti.pdf(2.36MB)
----Hypothesis Test One sample and two sample T Test .ipynb(30KB)
----Big Sales Mart Final Script.ipynb(477KB)
----Hierarchical clustering.pptx(3.54MB)
----Bayes Theorem and Probability - Day 03.html(405KB)
----10 Common Data Science Pitfalls.pdf(1.72MB)
----MNIST Dataset.ipynb(104KB)
----README.md(61B)
----Support Vector Machines.html(317KB)
----House Price Prediction Using PCA- Kaggle.ipynb(84KB)
----Chi_Square_Tests_Titanic_Dataset.ipynb(78KB)
----Ensemble Methods Part 02.ipynb(2.49MB)
----Data Visualisation Using Seaborn Python.html(996KB)
----M4W2 - Case study_SVM - Breast cancer.html(675KB)
----Sequential Feature Selector and Clustering on Titanic Dataset (1).ipynb(207KB)
----Hypothesis Testing - Summary.html(269KB)
----Lasso and Ridge Regression - Big Sales Mart Competition .ipynb(386KB)
----Continuous_Probability_Distribution Basicsl.ipynb(6KB)
----Unsupervised Day 3.html(996KB)
----Titanic ML with 0.80 Kaggle & RFE.ipynb(314KB)
----Hierarchical Clustering.ipynb(156KB)
----Introduction to Programming in Python.pdf(396KB)
----BigMart Sales Case Study - Final Script.ipynb(622KB)
----Placement Bootcamp - Day 01.html(314KB)
----Handling Imbalance Dataset.pdf(1.05MB)
----Applied Predictive Modelling Maxx Kuhnn.pdf(6.09MB)
----K Means Clustering.html(397KB)
----Case Study - DAY 01.ipynb(477KB)
----Classification Cancer Data - Final Script.ipynb(29KB)
----K Means Clustering.ipynb(119KB)
----PCA - Pulsar Star _ Support Vector Machines.html(540KB)
----Titanic ML with 0.80 Kaggle & RFE (1).ipynb(526KB)
----Share_Price_Prediction.ipynb(302KB)
----KNN Algorithm.pptx(7.44MB)
----Python Libraries for Interpretable Machine Learning.pdf(484KB)
----Linear Regression - TTest FTest & Assumptions.ipynb(213KB)
----Day 01 Ensemble Methods.ipynb(56KB)
----783.pdf(285KB)
----50 days of Machine Learning.pdf(11.07MB)
----Stacking on Boston_Dataset.ipynb(48KB)
----Naive Bayes Case Study.html(476KB)
----Python Online Workout.ipynb(26KB)
----Ensembles_credit.ipynb(44KB)
----Statistics - 01.ipynb(44KB)
----Hierarchical Clustering Day 02.ipynb(339KB)
----Statistics - 02.ipynb(114KB)
----Pratap Snacks FY20 Report.pdf(829KB)
----Ensemble Models Diabetes Dataset.ipynb(35KB)
----Chi_Square_Test-2.ipynb(53KB)