{"id":15674758,"url":"https://github.com/qinhanmin2014/machine-learning-in-action","last_synced_at":"2025-04-24T03:01:55.666Z","repository":{"id":38897884,"uuid":"161452957","full_name":"qinhanmin2014/Machine-Learning-in-Action","owner":"qinhanmin2014","description":"Source code from the book Machine Learning in Action, corrected the errors, updated according to python 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Machine Learning in Action\n\nSource code from the book Machine Learning in Action.\nipynb format \u0026 html format,\ncorrected the [errors](https://manning-content.s3.amazonaws.com/download/8/94d527f-01ea-4fe5-926a-9d0b77bed50e/Harrington_MachineLearninginAction_Err2.htm)\n(along with some errors found by myself),\nupdated according to python 3.X.\n\nMachine Learning in Action.pdf: pdf version of the book\n\nMLiA_SourceCode.zip: [Source code from the original author](https://www.manning.com/books/machine-learning-in-action) (.py format)\n\n- 02 Classifying with k-Nearest Neighbors [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/02%20Classifying%20with%20k-Nearest%20Neighbors/kNN.ipynb)]\n- 03 Splitting datasets one feature at a time decision trees [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/03%20Splitting%20datasets%20one%20feature%20at%20a%20time%20decision%20trees/trees.ipynb)]\n- 04 Classifying with probability theory naive Bayes [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/04%20Classifying%20with%20probability%20theory%20naive%20Bayes/bayes.ipynb)]\n- 05 Logistic regression [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/05%20Logistic%20regression/logRegres.ipynb)]\n- 06 Support vector machines [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/06%20Support%20vector%20machines/svmMLiA.ipynb)]\n- 07 Improving classification with the AdaBoost meta-algorithm [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/07%20Improving%20classification%20with%20the%20AdaBoost%20meta-algorithm/adaboost.ipynb)]\n- 08 Predicting numeric values regression [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/08%20Predicting%20numeric%20values%20regression/regression.ipynb)]\n- 09 Tree-based regression [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/09%20Tree-based%20regression/regTrees.ipynb)]\n- 10 Grouping unlabeled items using k-means clustering [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/10%20Grouping%20unlabeled%20items%20using%20k-means%20clustering/kMeans.ipynb)]\n- 11 Association analysis with the Apriori algorithm [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/11%20Association%20analysis%20with%20the%20Apriori%20algorithm/apriori.ipynb)]\n- 12 Efficiently finding frequent itemsets with FP-growth [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/12%20Efficiently%20finding%20frequent%20itemsets%20with%20FP-growth/fpGrowth.ipynb)]\n- 13 Using principal component analysis to simplify data [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/13%20Using%20principal%20component%20analysis%20to%20simplify%20data/pca.ipynb)]\n- 14 Simplifying data with the singular value decomposition [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/14%20Simplifying%20data%20with%20the%20singular%20value%20decomposition/svdRec.ipynb)]\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqinhanmin2014%2Fmachine-learning-in-action","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fqinhanmin2014%2Fmachine-learning-in-action","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqinhanmin2014%2Fmachine-learning-in-action/lists"}