https://github.com/qinhanmin2014/machine-learning-in-action

Source code from the book Machine Learning in Action, corrected the errors, updated according to python 3.X
https://github.com/qinhanmin2014/machine-learning-in-action

machine-learning machine-learning-algorithms

Last synced: about 1 year ago
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Source code from the book Machine Learning in Action, corrected the errors, updated according to python 3.X

• Host: GitHub
• URL: https://github.com/qinhanmin2014/machine-learning-in-action
• Owner: qinhanmin2014
• Created: 2018-12-12T08:00:30.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-03-03T11:58:42.000Z (over 7 years ago)
• Last Synced: 2025-03-30T06:13:45.181Z (over 1 year ago)
• Topics: machine-learning, machine-learning-algorithms
• Language: HTML
• Size: 72.6 MB
• Stars: 16
• Watchers: 1
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Machine Learning in Action

Source code from the book Machine Learning in Action.

ipynb format & html format,

corrected the [errors](https://manning-content.s3.amazonaws.com/download/8/94d527f-01ea-4fe5-926a-9d0b77bed50e/Harrington_MachineLearninginAction_Err2.htm)

(along with some errors found by myself),

updated according to python 3.X.

Machine Learning in Action.pdf: pdf version of the book

MLiA_SourceCode.zip: [Source code from the original author](https://www.manning.com/books/machine-learning-in-action) (.py format)

- 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)]

- 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)]

- 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)]

- 05 Logistic regression [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/05%20Logistic%20regression/logRegres.ipynb)]

- 06 Support vector machines [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/06%20Support%20vector%20machines/svmMLiA.ipynb)]

- 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)]

- 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)]

- 09 Tree-based regression [[notebook](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/09%20Tree-based%20regression/regTrees.ipynb)]

- 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)]

- 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)]

- 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)]

- 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)]

- 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)]