This project is focused on the characteristics of white wine quality. Mainly the wite wine quality dataset is explored and analysed.
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Updated
Aug 9, 2017 - HTML
This project is focused on the characteristics of white wine quality. Mainly the wite wine quality dataset is explored and analysed.
The fraud identification models were build using Python Scikit-learn machine-learning module.
Data: Boston Housing Dataset (HousingData.csv) Programming language(s): R Tool(s): RStudio Business problem: To understand the drivers behind the value of houses in Boston and provide data-driven recommendation to the client on how they can increase the value of housing.The Boston housing dataset consisted of 506 observations and 14 variables. P…
In this project, I predict which customers are more likely to respond positively to a bank marketing call by setting up a regular savings deposit or subscribing the term “made_deposit”. Three classification algorithms have been developed in order to predict the target variable. Logistic Regression, Decision Tree and Multi-Layer Perceptron (MLP).…
Classification of an imbalanced dataset using SMOTE oversampling technique and ML Algorithms - KNN , XGBoost and Naive Bayes classifier
Multi-label classification is one of the standard tasks in text analytics. The objective is to perform an eXtreme multi-label classification (XMLC) on two datasets( https://www.kaggle.com/hsrobo/titlebased-semantic-subject-indexing) -EconBiz( ZBW - Leibniz Information Centre for Economics from July 2017) and PubMed(5th BioASQ challenge on large-…
A Binary Classification Problem Optimized For AU-ROC Curve,. From Data Cleaning to Model Validation, Classifying whether a blight ticket will be paid in time or not, Trained 3 different Classifier on a Highly imbalanced Data provided by Detroit Open Data Portal with around 160000 Tickets.
In this project we can see in action and in detail a big part of the ML pipeline (data wrangling,model building, model evaluation) that comprises different algorithms and approaches such as Decision Trees (RPART), Linear Discriminant Analysis (LDA), Gradient Boosting Machne (GBM), Random Forest (RF) Support Vector Machine (SVM) with or without M…
A comprehensive analysis and modelling for the Titanic data, covering, data cleaning, outlier identification, EDA, feature engineering/selection, and model evaluation. Got top 15% as a result of this effort
Multi-Linear-Reg
Statistical Modelling of Swine Flu Outbreak Data
Tree-level completions of LNV operators for neutrino-mass model building
Runtime EntityFramework model builder from metadata tables. Provides a static usage at compile time via proxies classes. Created as CRM/ERP core.
machine learning projects and datasets
A collaborative list of awesome CryoEM (Cryo Electron Microscopy) resources.
Model Building and Testing using Ridge, Lasso and ElasticNet Methods
Jupyter Notebooks for visualizing and exploring empirical model building. http://charlesreid1.github.io/empirical-model-building
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