├── Data Prep ├── DataPrep.ipynb └── img │ ├── IQR.png │ ├── bar1.jpg │ ├── bar2.png │ ├── binning.png │ ├── cross_valid.png │ ├── cv.png │ ├── encode.png │ ├── flow.png │ ├── hist1.png │ ├── hist2.png │ ├── imbalance.png │ ├── logo.png │ ├── norm.png │ ├── skew.jpg │ ├── skew.png │ ├── split.png │ ├── stddev.png │ ├── stndr.png │ └── wordcloud.jpg ├── Decision Trees ├── datasets │ └── iris.csv ├── decision_trees.ipynb └── img │ ├── Decision_Tree.jpg │ ├── ensemble1.png │ ├── ensemble2.png │ ├── logo.png │ └── split.png ├── Linear Algebra ├── Linear_Algebra.ipynb └── img │ ├── linear.png │ └── logo.png ├── Linear Regression ├── img │ ├── lin1.png │ ├── logo.png │ └── residual-plot.png └── linear_regression.ipynb ├── Logistic Regression ├── img │ ├── acc.png │ ├── logis.jpg │ ├── logo.png │ ├── roc.png │ └── s.jpeg └── logistic_regression.ipynb ├── Probabilty ├── img │ ├── 1.png │ ├── bayes.jpeg │ ├── cond.png │ ├── cont1.jpg │ ├── continous.png │ ├── data.jpg │ ├── dis1.png │ ├── dis2.png │ ├── discont.png │ ├── discrete.png │ ├── distributionflowchart.png │ ├── logo.png │ ├── mar_prob.png │ └── overview-prob-distr.png └── probability.ipynb ├── Project ├── .ipynb_checkpoints │ ├── 09-11-2020 ML Course Nigeria Project 'name'-checkpoint.ipynb │ └── 19-11-2020 ML Course Nigeria Project 'name'-checkpoint.ipynb ├── 19-11-2020 ML Course Nigeria Project 'name'.ipynb └── winequality.csv ├── README.md ├── Regularization ├── datasets │ └── reg.csv ├── img │ ├── 1.PNG │ ├── 2.PNG │ ├── 3.PNG │ ├── 4.PNG │ ├── 5.PNG │ ├── 6.PNG │ ├── 7.png │ ├── 8.png │ └── logo.png └── regularization.ipynb └── Unsupervised Learning ├── img ├── 1.PNG ├── 10.PNG ├── 11.PNG ├── 2.PNG ├── 3.PNG ├── 4.PNG ├── 5.PNG ├── 6.PNG ├── 7.PNG ├── 8.PNG ├── 9.PNG └── sil.jpeg └── unsupervised_learning.ipynb /Data Prep/DataPrep.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/KutayAkalin/ML_Course_19-11-20/HEAD/Data 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