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This project is a part of research on Breast Cancer Diagnosis with a Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.
Desafio de clusterização de clientes feito para o IFood e Tera. Utilizando as bibliotecas Plotly, Sklearn e Yellowbrick conseguimos fazer a clusterização em 3 dimensões de forma eficiente e visual utilizando as features construídas no feature engineering a partir de bases de clientes, pedidos e sessões do iFood.
This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset
Exploratory Data Analysis (EDA) is one of the techniques used for extracting vital features and trends used by machine learning and deep learning models in Data Science
It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.
This project is a part of research on Breast Cancer Diagnosis with Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.