| 8. K-Means-Customer-Seg.ipynb | 375.1 KB | |
| 9.Hierarchical-Clustering.ipynb | 98.2 KB | |
| Credit card fraud detection.ipynb | 890.9 KB | |
| Cust_Segmentation.xlsx | 56.4 KB | |
| Decision Tree.ipynb | 489.5 KB | |
| Default Modelling using logistic regression.ipynb | 141.4 KB | |
| EDAcarsales.ipynb | 167 KB | |
| Image recognition using neural network .ipynb | 115.2 KB | |
| Introduction to Ensembling methods.ipynb | 896.9 KB | |
| K-Means random.ipynb | 73.8 KB | |
| K-Means.ipynb | 1 MB | |
| K-means Customer Segmentation .ipynb | 220.6 KB | |
| KNN with case study.ipynb | 131.9 KB | |
| Linear Regression-1.ipynb | 339.1 KB | |
| Linear Regression.ipynb | 207.2 KB | |
| Logistic Regression.ipynb | 78.3 KB | |
| ML Introduction treating a DataSet.ipynb | 576.3 KB | |
| Naïve Bayes introduction and example demonstration.ipynb | 137.3 KB | |
| Neural Network.ipynb | 135.2 KB | |
| Neural Network2.ipynb | 676.9 KB | |
| POC CO2 emission.ipynb | 397.4 KB | |
| Random Forest Continuous data.ipynb | 60.5 KB | |
| Random Forest.ipynb | 243.7 KB | |
| SVM.ipynb | 588.4 KB | |
| Text Mining.ipynb | 376.2 KB | |
| Undersatnding Linear Regression.ipynb | 537 KB | |
| Use Case Linear Regression.ipynb | 248.4 KB | |
| cars_clus.csv | 17.7 KB | |
| dummy | 1 bytes | |
| naivebayes.pickle | 8 MB | |
