GitHub - Metallicode/Math: AI oriented Math Projects

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Name		Name	Last commit message	Last commit date
Latest commit History 109 Commits
Bayes_NLP.ipynb		Bayes_NLP.ipynb
Boosting_Methods.ipynb		Boosting_Methods.ipynb
CIFAR_10_dataset.ipynb		CIFAR_10_dataset.ipynb
Categorical_Data_Encoding.ipynb		Categorical_Data_Encoding.ipynb
Choosing_The_Polynomial_Degree.ipynb		Choosing_The_Polynomial_Degree.ipynb
Composite_Functions.ipynb		Composite_Functions.ipynb
Covariance_And_Correlation.ipynb		Covariance_And_Correlation.ipynb
Cross_Validation.ipynb		Cross_Validation.ipynb
DBSCAN_Hyper_Parameters.ipynb		DBSCAN_Hyper_Parameters.ipynb
Data_Presentation.ipynb		Data_Presentation.ipynb
Decision_Tree_Intro.ipynb		Decision_Tree_Intro.ipynb
Discontinuous_Functions.ipynb		Discontinuous_Functions.ipynb
Feature_Engineering.ipynb		Feature_Engineering.ipynb
Feature_Scaling.ipynb		Feature_Scaling.ipynb
Function_Symmetry.ipynb		Function_Symmetry.ipynb
Gradient_Boosting.ipynb		Gradient_Boosting.ipynb
Grid_Search.ipynb		Grid_Search.ipynb
Hierarchical_Clustering.ipynb		Hierarchical_Clustering.ipynb
Hierarchical_Clustering_Distance_Metrics.ipynb		Hierarchical_Clustering_Distance_Metrics.ipynb
Intro_To_LSTM.ipynb		Intro_To_LSTM.ipynb
Intro_To_RNN.ipynb		Intro_To_RNN.ipynb
Intro_to_sklearn.ipynb		Intro_to_sklearn.ipynb
Introduction_To_PCA.ipynb		Introduction_To_PCA.ipynb
Introduction_to_DBSCAN.ipynb		Introduction_to_DBSCAN.ipynb
KNN_Model_Optimization.ipynb		KNN_Model_Optimization.ipynb
K_Means_Clustering.ipynb		K_Means_Clustering.ipynb
K_Means_Clustering_Intro.ipynb		K_Means_Clustering_Intro.ipynb
K_Nearest_Neighbors.ipynb		K_Nearest_Neighbors.ipynb
Kares_Basics.ipynb		Kares_Basics.ipynb
Keras_Basic_Classification.ipynb		Keras_Basic_Classification.ipynb
Keras_Basic_Regression.ipynb		Keras_Basic_Regression.ipynb
Linear_Regression.ipynb		Linear_Regression.ipynb
Logistic_Regression_theory.ipynb		Logistic_Regression_theory.ipynb
Logistic_Regression_with_sklearn.ipynb		Logistic_Regression_with_sklearn.ipynb
MAE_Vs_MSE.ipynb		MAE_Vs_MSE.ipynb
MNIST.ipynb		MNIST.ipynb
Multi_Class_Logistic_Regression.ipynb		Multi_Class_Logistic_Regression.ipynb
Naive_Bayes_classifier_theory.ipynb		Naive_Bayes_classifier_theory.ipynb
Piecewise_Functions.ipynb		Piecewise_Functions.ipynb
Polynomial_Regression.ipynb		Polynomial_Regression.ipynb
Power_and_Log_Rules.ipynb		Power_and_Log_Rules.ipynb
RNN_on_a_Sine_Wave.ipynb		RNN_on_a_Sine_Wave.ipynb
Random_Forests_Regression.ipynb		Random_Forests_Regression.ipynb
Random_Forests_classification.ipynb		Random_Forests_classification.ipynb
Regression_Models_Overview.ipynb		Regression_Models_Overview.ipynb
Regularization.ipynb		Regularization.ipynb
SVM_Regression.ipynb		SVM_Regression.ipynb
Sklearn_Decision_Trees.ipynb		Sklearn_Decision_Trees.ipynb
Sklearn_Perceptron.ipynb		Sklearn_Perceptron.ipynb
Support_Vector_Machines_basic_theory.ipynb		Support_Vector_Machines_basic_theory.ipynb
Text_Classification_With_Sklearn.ipynb		Text_Classification_With_Sklearn.ipynb
Text_Feature_Extraction_With_Sklearn.ipynb		Text_Feature_Extraction_With_Sklearn.ipynb
Trigonometric_Functions.ipynb		Trigonometric_Functions.ipynb
Using_Clustering_For_Preprocessing.ipynb		Using_Clustering_For_Preprocessing.ipynb
e.ipynb		e.ipynb
intro_to_pandas.ipynb		intro_to_pandas.ipynb
readme		readme