- This contains all my projects for Data Science, NLP and Machine Learning.
- Done with Jupyter notebook.
- And PYTHON is my favourite language.
- Frequently used stats : [StatsExplained] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/StatsExplained/StatsExplained.ipynb)
- Undersampling, Oversampling and SMOTE : [imbalanceData] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/imbalancedDATA/Imbalanced%20Data.ipynb)
- PCA : [PCA-logic] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/DimensionallityReduction/PCA/PCA_intiution.ipynb)
- Recduce using T-SNE : [T-sne] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/DimensionallityReduction/Untitled.ipynb)
- Linear regression
- Logistic
- Steps to simple Kmeans-Clustering : [K-means] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/CLustering/K-means/Kmeans%20Clustering.ipynb)
- Hierarchical Clustering : [MeanShift-clustering] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/CLustering/Hierarchical%20clustering/H_clustering.ipynb)
- Silhouette analysis for Kmeans : [Silhouette] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/CLustering/ClusteringProject/Insurance_clustering.ipynb)
- Starting with time-series : [Airdata-time-series] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/Time%20series/Time%20Series/Untitled.ipynb)
- Time-series : [Tractor-data-time-series] (https://github.com/sam2015/Machine_Learning/blob/master/Time%20series/Tractor_Ivy_Time%20series/Untitled.ipynb)
- Analysing with food-odering data : [Cohort] (http://nbviewer.jupyter.org/github/sam2015/Machine_Learning/blob/master/Cohort%20Analysis/Untitled.ipynb)