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Regression, Classification, Clustering, Dimension-reduction, Anomaly detection

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All_ML_Classification_Models
All_ML_Classification_Models
 
 
All_ML_Clustering_models
All_ML_Clustering_models
 
 
All_ML_Regression_Models
All_ML_Regression_Models
 
 
Assignments
Assignments
 
 
AutoML
AutoML
 
 
Feature_Engineering
Feature_Engineering
 
 
Feature_Selection
Feature_Selection
 
 
Handle_Imbalance
Handle_Imbalance
 
 
MultiLabelClassification
MultiLabelClassification
 
 
Bias_Data.ipynb
Bias_Data.ipynb
 
 
Classifier : End_to_End_Classification_model_Analysis.ipynb
Classifier : End_to_End_Classification_model_Analysis.ipynb
 
 
Classifier: Benchmarking_XGBoost_on_GPU.ipynb
Classifier: Benchmarking_XGBoost_on_GPU.ipynb
 
 
Classifier: Comparing_Classifications_Models.ipynb
Classifier: Comparing_Classifications_Models.ipynb
 
 
Classifier: Decision_tree.ipynb
Classifier: Decision_tree.ipynb
 
 
Classifier: Light_GBM.ipynb
Classifier: Light_GBM.ipynb
 
 
Classifier: NaiveBayesModel_CountVectorizer_email_spam_filter.ipynb
Classifier: NaiveBayesModel_CountVectorizer_email_spam_filter.ipynb
 
 
Classifier: Types_of_Cross_Validation.ipynb
Classifier: Types_of_Cross_Validation.ipynb
 
 
Classifier: XGBoost_SparkML_GPU_Colab_Python.ipynb
Classifier: XGBoost_SparkML_GPU_Colab_Python.ipynb
 
 
Classifier_AdaboostClassifier_Telecom_Data.ipynb
Classifier_AdaboostClassifier_Telecom_Data.ipynb
 
 
Clustering: GMM(Gaussian_Mixture_Model).ipynb
Clustering: GMM(Gaussian_Mixture_Model).ipynb
 
 
Data_Train.xlsx
Data_Train.xlsx
 
 
DimReduction: PCA.ipynb
DimReduction: PCA.ipynb
 
 
DimReduction: PCA_digits.ipynb
DimReduction: PCA_digits.ipynb
 
 
Ensemble: Clf_Custom_Ensemble_Model.ipynb
Ensemble: Clf_Custom_Ensemble_Model.ipynb
 
 
Ensemble: Stacking_Custom_Ensemble_Machine_Learning.ipynb
Ensemble: Stacking_Custom_Ensemble_Machine_Learning.ipynb
 
 
README.md
README.md
 
 
Regressor: CatBoost_Regressor.ipynb
Regressor: CatBoost_Regressor.ipynb
 
 
Regressor: ML_Taxi_dataset_XGB_with_SKL_pipeline.ipynb
Regressor: ML_Taxi_dataset_XGB_with_SKL_pipeline.ipynb
 
 
Regressor_RandomForestFlightPricePrediction.ipynb
Regressor_RandomForestFlightPricePrediction.ipynb
 
 
Regressor_RandomForest_CarPricePrediction.ipynb
Regressor_RandomForest_CarPricePrediction.ipynb
 
 
Test_set.xlsx
Test_set.xlsx
 
 
car data.csv
car data.csv
 
 
telecom_users.csv
telecom_users.csv
 
 

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ML-Algos

In this repository, I would talk about various interesting Machine Learning Regression, Classification and Clustering Algorithm codes in Python and some assignment based on ML algos.

New evolving libraries on ML will be added over time: Following are available:

#lazypredict

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Regression, Classification, Clustering, Dimension-reduction, Anomaly detection

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clustering regression xgboost pca classification lightgbm adaboost gmm folium dbscan umap stacking gradient-boosting boosting hdbscan bagging catboost gmm-clustering crossvalidation dimentionality-reduction

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