├── 0204 - Navigating the Spyder & Jupyter Notebook Interface.zip ├── 0205 - Downloading the IRIS Datasets.zip ├── 0206 - Data Exploration and Analysis.zip ├── 0207 - Presenting Your Data.zip ├── 0303 - Working with Scikit-Learn.zip ├── 0304 - Boston Housing Data - EDA.zip ├── 0305 - Correlation Analysis and Feature Selection.zip ├── 0306 - Simple Linear Regression Modelling with Boston Housing Data.zip ├── 0307 - Robust Regression.zip ├── 0308 - Evaluate Model Performance.zip ├── 0309 - Multiple Regression with statsmodel.zip ├── 0310 - Multiple Regression and Feature Importance.zip ├── 0311 - Ordinary Least Square Regression and Gradient Descent.zip ├── 0312 - Regularised Method for Regression.zip ├── 0313 - Polynomial Regression.zip ├── 0314 - Dealing with Non-linear relationships.zip ├── 0315 - Feature Importance Revisited.zip ├── 0316 - Data Pre-Processing 1.zip ├── 0317 - Data Pre-Processing 2.zip ├── 0318 - Variance Bias Trade Off - Validation Curve.zip ├── 0319 - Variance Bias Trade Off - Learning Curve.zip ├── 0320 - Cross Validation.zip ├── 04-02-MNIST(openml).ipynb ├── 0403 - Logistic Regression 1.zip ├── 0404 - Logistic Regression 2.zip ├── 0405 - MNIST Project 1 - Introduction.zip ├── 0406 - MNIST Project 2 - SGDClassifier.zip ├── 0407 - MNIST Project 3 - Performance Measures.zip ├── 0408 - MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score.zip ├── 0409 - MNIST Project 5 - Precision and Recall Tradeoff.zip ├── 0410 - MNIST Project 6 - The ROC Curve.zip ├── 0502 - Linear SVM Classification.zip ├── 0503 - Polynomial Kernel.zip ├── 0504 - Gaussian Radial Basis Function.zip ├── 0505 - Support Vector Regression.zip ├── 0506 - Advantage and Disadvantages of SVM.zip ├── 0602 - What is Decision Tree.zip ├── 0603 - Training a Decision Tree.zip ├── 0604 - Visualising a Decision Trees.zip ├── 0605 - Decision Tree Learning Algorithm.zip ├── 0606 - Decision Tree Regression.zip ├── 0607 - Overfitting and Grid Search.zip ├── 0608 - Where to From Here.zip ├── 0609 - Project HR - Loading and preprocesing data.zip ├── 0610 - Project HR - Modelling.zip ├── 0702 - Ensemble Learning Methods Introduction.zip ├── 0703 - Bagging Part 1.zip ├── 0704 - Bagging Part 2.zip ├── 0705 - Random Forests.zip ├── 0706 - Extra-Trees.zip ├── 0707 - AdaBoost.zip ├── 0708 - Gradient Boosting Machine.zip ├── 0709 - XGBoost.zip ├── 0710 - Project HR - Human Resources Analytics.zip ├── 0711 - Ensemble of ensembles 1.zip ├── 0712 - Ensemble of ensembles 2.zip ├── 0802 - k-Nearest Neighbour Concepts.zip ├── 0803 - kNN and IRIS demo.zip ├── 0805 - Project Cancer Detection 1.zip ├── 0806 - Project Cancer Detection 2.zip ├── 0902 - Dimensionality Reduction Concept .zip ├── 0903 - PCA Introduction .zip ├── 0906 - Project Wine 2 Choosing the Number of Components .zip ├── 0907 - Kernel PCA .zip ├── 0908 - Kernel PCA Demo .zip ├── 0909 - LDA & Comparison between LDA and PCA .zip ├── 1002 - Clustering.zip ├── Code snippets.ipynb └── README.md /0204 - Navigating the Spyder & Jupyter Notebook Interface.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0204 - 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Presenting Your Data.zip -------------------------------------------------------------------------------- /0303 - Working with Scikit-Learn.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0303 - Working with Scikit-Learn.zip -------------------------------------------------------------------------------- /0304 - Boston Housing Data - EDA.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0304 - Boston Housing Data - EDA.zip -------------------------------------------------------------------------------- /0305 - Correlation Analysis and Feature Selection.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0305 - Correlation Analysis and Feature Selection.zip -------------------------------------------------------------------------------- /0306 - Simple Linear Regression Modelling with Boston Housing Data.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0306 - Simple Linear Regression Modelling with Boston Housing Data.zip -------------------------------------------------------------------------------- /0307 - Robust Regression.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0307 - Robust Regression.zip -------------------------------------------------------------------------------- /0308 - Evaluate Model Performance.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0308 - Evaluate Model Performance.zip -------------------------------------------------------------------------------- /0309 - Multiple Regression with statsmodel.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0309 - Multiple Regression with statsmodel.zip -------------------------------------------------------------------------------- /0310 - Multiple Regression and Feature Importance.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0310 - Multiple Regression and Feature Importance.zip -------------------------------------------------------------------------------- /0311 - Ordinary Least Square Regression and Gradient Descent.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0311 - Ordinary Least Square Regression and Gradient Descent.zip -------------------------------------------------------------------------------- /0312 - Regularised Method for Regression.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0312 - Regularised Method for Regression.zip -------------------------------------------------------------------------------- /0313 - Polynomial Regression.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0313 - Polynomial Regression.zip -------------------------------------------------------------------------------- /0314 - Dealing with Non-linear relationships.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0314 - Dealing with Non-linear relationships.zip -------------------------------------------------------------------------------- /0315 - Feature Importance Revisited.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0315 - Feature Importance Revisited.zip -------------------------------------------------------------------------------- /0316 - Data Pre-Processing 1.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0316 - Data Pre-Processing 1.zip -------------------------------------------------------------------------------- /0317 - Data Pre-Processing 2.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0317 - Data Pre-Processing 2.zip -------------------------------------------------------------------------------- /0318 - Variance Bias Trade Off - Validation Curve.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0318 - Variance Bias Trade Off - Validation Curve.zip -------------------------------------------------------------------------------- /0319 - Variance Bias Trade Off - Learning Curve.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0319 - Variance Bias Trade Off - Learning Curve.zip -------------------------------------------------------------------------------- /0320 - Cross Validation.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0320 - Cross Validation.zip -------------------------------------------------------------------------------- /04-02-MNIST(openml).ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/04-02-MNIST(openml).ipynb -------------------------------------------------------------------------------- /0403 - Logistic Regression 1.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0403 - Logistic Regression 1.zip -------------------------------------------------------------------------------- /0404 - Logistic Regression 2.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0404 - Logistic Regression 2.zip -------------------------------------------------------------------------------- /0405 - MNIST Project 1 - Introduction.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0405 - MNIST Project 1 - Introduction.zip -------------------------------------------------------------------------------- /0406 - MNIST Project 2 - SGDClassifier.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0406 - MNIST Project 2 - SGDClassifier.zip -------------------------------------------------------------------------------- /0407 - MNIST Project 3 - Performance Measures.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0407 - MNIST Project 3 - Performance Measures.zip -------------------------------------------------------------------------------- /0408 - MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0408 - MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score.zip -------------------------------------------------------------------------------- /0409 - MNIST Project 5 - Precision and Recall Tradeoff.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0409 - MNIST Project 5 - Precision and Recall Tradeoff.zip -------------------------------------------------------------------------------- /0410 - MNIST Project 6 - The ROC Curve.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0410 - MNIST Project 6 - The ROC Curve.zip -------------------------------------------------------------------------------- /0502 - Linear SVM Classification.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0502 - Linear SVM Classification.zip -------------------------------------------------------------------------------- /0503 - Polynomial Kernel.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0503 - Polynomial Kernel.zip -------------------------------------------------------------------------------- /0504 - Gaussian Radial Basis Function.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0504 - Gaussian Radial Basis Function.zip -------------------------------------------------------------------------------- /0505 - Support Vector Regression.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0505 - Support Vector Regression.zip -------------------------------------------------------------------------------- /0506 - Advantage and Disadvantages of SVM.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0506 - Advantage and Disadvantages of SVM.zip -------------------------------------------------------------------------------- /0602 - What is Decision Tree.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0602 - What is Decision Tree.zip -------------------------------------------------------------------------------- /0603 - Training a Decision Tree.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0603 - Training a Decision Tree.zip -------------------------------------------------------------------------------- /0604 - Visualising a Decision Trees.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0604 - Visualising a Decision Trees.zip -------------------------------------------------------------------------------- /0605 - Decision Tree Learning Algorithm.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0605 - Decision Tree Learning Algorithm.zip -------------------------------------------------------------------------------- /0606 - Decision Tree Regression.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0606 - Decision Tree Regression.zip -------------------------------------------------------------------------------- /0607 - Overfitting and Grid Search.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0607 - Overfitting and Grid Search.zip -------------------------------------------------------------------------------- /0608 - Where to From Here.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0608 - 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Extra-Trees.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0706 - Extra-Trees.zip -------------------------------------------------------------------------------- /0707 - AdaBoost.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0707 - AdaBoost.zip -------------------------------------------------------------------------------- /0708 - Gradient Boosting Machine.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0708 - Gradient Boosting Machine.zip -------------------------------------------------------------------------------- /0709 - XGBoost.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0709 - 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PCA Introduction .zip -------------------------------------------------------------------------------- /0906 - Project Wine 2 Choosing the Number of Components .zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0906 - Project Wine 2 Choosing the Number of Components .zip -------------------------------------------------------------------------------- /0907 - Kernel PCA .zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0907 - Kernel PCA .zip -------------------------------------------------------------------------------- /0908 - Kernel PCA Demo .zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/anthonyng2/udemy-the-complete-machine-learning-course-with-python/HEAD/0908 - 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