Machine Learning Model helps to gain an understanding of how to optimize a number of models using grid searching
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Updated
Jul 19, 2019 - HTML
Machine Learning Model helps to gain an understanding of how to optimize a number of models using grid searching
Identifies the parts of the Germany population that best describe the core customer base of the Arvato company. Uses a supervised model to predict which individuals are most likely to convert into becoming customers for the company.
Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).
Analyse the factors which lead to online shopping on a website and building predictive models for it.
Implementation of various machine learning algorithms from scratch.
Identify fraudulent credit card transactions.
Using Decision Tree and AdaBoost to classify languages(English/Dutch)
A Project to leverage machine learning algorithms to predict the potential donors based on a number of features.
Automobile dataset for used Car Price Analysis to predict the price of a vehicle with their features and performance factor to provide the exact value of a vehicle for buyer seller satisfaction using exploratory data analysis and machine learning models.
Perceptron Implementation - implementing Empirical Risk Minimization (ERM) and k-folds cross-validation
Implementation of common ML Algorithms from scratch in Python3
Using DCGAN and Ensemble Learning to classify the difference of the disease of different mangoes.
Employee-Absenteeism-Project-Work
Using Various Regression Algorithms to Predict House Sales
Implementation of several ML models like decision tree, linear regression, ensemble methods, etc.
Image processing algorithms
Image classification using SVM, KNN, Bayes, Adaboost, Random Forest and CNN.Extracting features and reducting feature dimension using T-SNE, PCA, LDA.
Implementation of an adaboost algorithm on the dataset HC_Body_Temperature
A simple example project on XGBoost and Adaboost.
This project is about to classify if an event is terrorist or other forms of crime as per the Global Standards.
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