ML_selfteaching

This is a dump of all my Jupyter Notebooks, with Exploratory Data Analysis for different datasets as well as self-familirisation with different concepts

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
10[desiciontree&label encoding].ipynb		10[desiciontree&label encoding].ipynb
11[SVM for digits dataset].ipynb		11[SVM for digits dataset].ipynb
11[svm].ipynb		11[svm].ipynb
12[kfolds].ipynb		12[kfolds].ipynb
14[kmeans].ipynb		14[kmeans].ipynb
15[email classifcation].ipynb		15[email classifcation].ipynb
15[naive bayes].ipynb		15[naive bayes].ipynb
17[gridsearch].ipynb		17[gridsearch].ipynb
18[l1 + l2 reg].ipynb		18[l1 + l2 reg].ipynb
19[PCA].ipynb		19[PCA].ipynb
21[ensemble bagging.ipynb		21[ensemble bagging.ipynb
6[dummyvariables].ipynb		6[dummyvariables].ipynb
7[training&testing].ipynb		7[training&testing].ipynb
HR EDA.ipynb		HR EDA.ipynb
HR_comma_sep.csv		HR_comma_sep.csv
README.md		README.md
coolcommands.ipynb		coolcommands.ipynb
graddescent[4].ipynb		graddescent[4].ipynb
gridsearch for digits.ipynb		gridsearch for digits.ipynb
heart disease eda.ipynb		heart disease eda.ipynb
heart.csv		heart.csv
kmeans_iris_dataset.ipynb		kmeans_iris_dataset.ipynb
logsiticregression[8].ipynb		logsiticregression[8].ipynb
model_pickle		model_pickle
multiclass using digits[9].ipynb		multiclass using digits[9].ipynb
multivariate[3].ipynb		multivariate[3].ipynb
multivariate_model[2].ipynb		multivariate_model[2].ipynb
nb_wineclassification.ipynb		nb_wineclassification.ipynb
predicting titanic survivors using tree.ipynb		predicting titanic survivors using tree.ipynb
titanic.csv		titanic.csv

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