Machine Learning Models Repository

This repository contains a collection of machine learning models implemented in Python. The models cover various tasks, including clustering, regression, and classification, using popular libraries such as Scikit-learn, TensorFlow, and Keras.

Features

Clustering Models:
- K-Means Clustering
- Hierarchical Clustering
Regression Models:
- Linear Regression
- Decision Tree Regression
- Random Forest Regression
Classification Models:
- Logistic Regression
- Support Vector Machines (SVM)
- Neural Networks

Requirements

Python (version 3.6 or higher)
NumPy
Pandas
Scikit-learn
Matplotlib
TensorFlow or Keras (for neural networks)

Clone the repository:

git clone https://github.com/parth354/ML_Models.git
cd ML_Models

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Machine Learning Models Repository

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Name		Name	Last commit message	Last commit date
Apriori_(Association_Rule_Learning).ipynb		Apriori_(Association_Rule_Learning).ipynb
Artificial_Neural_Network(ANN).ipynb		Artificial_Neural_Network(ANN).ipynb
Convolutional_Neural_Networks_(CNN).ipynb		Convolutional_Neural_Networks_(CNN).ipynb
Decision_Tree_Classification(Classification).ipynb		Decision_Tree_Classification(Classification).ipynb
Decision_Tree_Regressor_Model.ipynb		Decision_Tree_Regressor_Model.ipynb
Eclat_Model.ipynb		Eclat_Model.ipynb
Grid_Search.ipynb		Grid_Search.ipynb
Hierarchial_Clustering.ipynb		Hierarchial_Clustering.ipynb
K_Means_Clustering.ipynb		K_Means_Clustering.ipynb
K_Nearest_Neighbors_Model(Classifier).ipynb		K_Nearest_Neighbors_Model(Classifier).ipynb
Kernel_PCA.ipynb		Kernel_PCA.ipynb
Kernel_SVM_(Classifier).ipynb		Kernel_SVM_(Classifier).ipynb
Linear_Discriminant_Analysis(LDA).ipynb		Linear_Discriminant_Analysis(LDA).ipynb
Logistic_Regression_Model_(Classification).ipynb		Logistic_Regression_Model_(Classification).ipynb
Multiple_Linear_Regression.ipynb		Multiple_Linear_Regression.ipynb
NLP_(Bag_Of_Words).ipynb		NLP_(Bag_Of_Words).ipynb
Naive_Bayes_(Classification).ipynb		Naive_Bayes_(Classification).ipynb
Polynomial_Linear_Regression_Model.ipynb		Polynomial_Linear_Regression_Model.ipynb
Principal_Component_Analysis(Dimensionality_Reduction).ipynb		Principal_Component_Analysis(Dimensionality_Reduction).ipynb
README.md		README.md
Random_Forest_(Classification).ipynb		Random_Forest_(Classification).ipynb
Random_Forest_Regression_Model.ipynb		Random_Forest_Regression_Model.ipynb
Simple_Linear_Regression_Model.ipynb		Simple_Linear_Regression_Model.ipynb
Support_Vector_Machine(Classifier).ipynb		Support_Vector_Machine(Classifier).ipynb
Support_Vector_Regression.ipynb		Support_Vector_Regression.ipynb
Thompson_Sampling_(Reinforcement_Learning).ipynb		Thompson_Sampling_(Reinforcement_Learning).ipynb
UCB_Reinforcement_Learning.ipynb		UCB_Reinforcement_Learning.ipynb
XG_Boost.ipynb		XG_Boost.ipynb
k_Fold_Cross_Validation.ipynb		k_Fold_Cross_Validation.ipynb
ml_data_preprocessing.ipynb		ml_data_preprocessing.ipynb

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