Implémentation des algorithmes simples de Data Science
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Updated
May 7, 2019 - Jupyter Notebook
Implémentation des algorithmes simples de Data Science
This is a blog of how machine learning algorithms are used to detect if a person is prone to heart disease or not.
As an early diagnosis step machine learning classifiaction algorithms could be used in finding if the patient is prone to parkinsons disease.
This repository consists the Jupyter Notebook files containing code of Artificial Neural Network with different tuning parameters for a similar scenario.
Code accompanying my Medium articles
Predicting Math Scores for Brazilian high School National Exams
Code templates for different ML algorithms
Data collected from the patients of Sylhet Diabetes Hospital, Bangladesh.
Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.
Different Techniques to Handle Imbalanced Data Set
This repository containes one of the assignments I have submitted for my Machine Learning Course, precisely it containes the code to address a classification tasks using Sklearn and Support Vector Machines!
churn prediction for telecom company
Implemented SVC on the Olivetti dataset to predict if a person is wearing glasses or not by using cross-validation techniques in depth.
Machine Learning Models for Absenteeism at Work Dataset
Recommendation Systems
Random Forest Classification
Avaliação de vários algoritmos supervisionados realizando Tuning dos parâmetros com GridSearchCV
Collection of Python scripts
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