wjddyd66 / handson

HandsOn Category

Theory

1. Machine Learning-Theory1.Motivations and Basics
2. Machine Learning-Theory2.Fundamentals of Machine Learning
3. Machine Learning-Theory3.Naive Bayes Classifier
4. Machine Learning-Theory4.Logistic Regression
5. Machine Learning-Theory5.SVM
6. Machine Learning-Theory6.Training Testing and Regularization
7. Machine Learning-Theory7.Bayesian Classifier
8. Machine Learning-Theory8.K-Means Clustering and Gaussian Mixture Model
9. Machine Learning-Theory9.Hidden Markov Model

HandsOn

1. Appendix1.Numpy
2. Appendix2.Pandas
3. Appendix3.Matplotlib
4. Appendix4.Linear Algebra
5. HandsOn-Ch1.The_Machine_Learning_Landscape
6. HandsOn-Ch2.End_To_End_Machine_Learning_Project
7. HandsOn-Ch3.Classification
8. HandsOn-Ch4.Training_Linear_Models
9. HandsOn-Ch5.Support_Vector_Machine
10. HandsOn-Ch6.Decision_Tree
11. HandsOn-Ch7.Ensemble_Learning_and_Random_Forest
12. HandsOn-Ch8.Dimensionality_Reduction
13. HandsOn-Ch9.Dimensionality_Reduction2

각코드에 대한 자세한 내용

• Theory: https://wjddyd66.github.io/categories/#machine-learning
• HandsOn: https://wjddyd66.github.io/categories/#handson

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