MachineLearningModels

It's the repository of different machine learning models. It will have basic machine learning models template coded in python using google colab.

Machine Learning Regression models: Regression model can be linear and non linear can be used to predict real value.It has dependent and independed variables. If the independednt varialble is time , we are predicting future values . we can also predict unknown values with the regression models.

1.Simple Linear Regression y= b0 + c*x1

Ordinary Least square: BestFitting Line Sum(y -y')2 -->min

2.Multiple Linear Regression 3.Polynomial Regression 4.Support Vector for Regression (SVR) 5.Decision Tree Classification 6.Random Forest Classification

Name		Name	Last commit message	Last commit date
Machine Learning(Model Selection)		Machine Learning(Model Selection)
data		data
Apriori.ipynb		Apriori.ipynb
Artificial_neural_network.ipynb		Artificial_neural_network.ipynb
Computation_with_NumPy_and_N_Dimensional_Arrays_(start).ipynb		Computation_with_NumPy_and_N_Dimensional_Arrays_(start).ipynb
Copy_of_k_fold_cross_validation.ipynb		Copy_of_k_fold_cross_validation.ipynb
Copy_of_k_means_clustering.ipynb		Copy_of_k_means_clustering.ipynb
Data_preprocessing_tools1.ipynb		Data_preprocessing_tools1.ipynb
Decision_tree_classification.ipynb		Decision_tree_classification.ipynb
Decision_tree_regression.ipynb		Decision_tree_regression.ipynb
Eclat.ipynb		Eclat.ipynb
Google_Play_Store_App_Analytics.ipynb		Google_Play_Store_App_Analytics.ipynb
Grid_search.ipynb		Grid_search.ipynb
Hierarchical_clustering.ipynb		Hierarchical_clustering.ipynb
K_means_clustering.ipynb		K_means_clustering.ipynb
K_nearest_neighbors.ipynb		K_nearest_neighbors.ipynb
Kernel_pca.ipynb		Kernel_pca.ipynb
Lego_Analysis_for_Course_(start).ipynb		Lego_Analysis_for_Course_(start).ipynb
Linear_discriminant_analysis.ipynb		Linear_discriminant_analysis.ipynb
Logistic_regression.ipynb		Logistic_regression.ipynb
Multiple_linear_regression.ipynb		Multiple_linear_regression.ipynb
Naive_bayes.ipynb		Naive_bayes.ipynb
Nobel_Prize_Analysis_(start).ipynb		Nobel_Prize_Analysis_(start).ipynb
Polynomial_regression.ipynb		Polynomial_regression.ipynb
Principal_component_analysis.ipynb		Principal_component_analysis.ipynb
Programming_Languages_Analysis.ipynb		Programming_Languages_Analysis.ipynb
QueryResults_language.csv		QueryResults_language.csv
README.md		README.md
Random_forest_regression.ipynb		Random_forest_regression.ipynb
Salary_Analysis.ipynb		Salary_Analysis.ipynb
Seaborn_and_Linear_Regression_(start).ipynb		Seaborn_and_Linear_Regression_(start).ipynb
Simple_linear_regression.ipynb		Simple_linear_regression.ipynb
Support_vector_machine.ipynb		Support_vector_machine.ipynb
Thompson_sampling.ipynb		Thompson_sampling.ipynb
Upper_confidence_bound.ipynb		Upper_confidence_bound.ipynb
Xg_boost.ipynb		Xg_boost.ipynb
convolutional_neural_network.ipynb		convolutional_neural_network.ipynb
data_preprocessing_tools.ipynb		data_preprocessing_tools.ipynb
kernel_svm.ipynb		kernel_svm.ipynb
salaries_by_college_major		salaries_by_college_major
salaries_by_college_major.csv		salaries_by_college_major.csv
support_vector_regression.ipynb		support_vector_regression.ipynb

Navigation Menu

Repository files navigation

MachineLearningModels

About

Releases

Packages

Contributors

Languages

Latest commit

History

Folders and files

Repository files navigation

MachineLearningModels

About

Resources

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages