Proyecto de Datacamp sobre predicción de dias en que un cliente alquilará un DVD basandose en algunas caracteristicas

machine learning regression

Exploratory data analysis exercises to understand the main characteristics of a given data set before performing more advanced analysis or further modeling

Analyzing a dataset of bank transactions and using gradient boosting classifier to capture as many fraudulent transactions as possible while minimizing false positives.

Predict precipitation to mitigate flood damage in Bangladesh

Developed a predictive model for heart disease using Decision Tree Algorithm to provide early diagnosis, performed Exploratory Data Analysis to find out the exact affecting symptom , visualized the data set using Matplolib, seaborn libraries For improving performance of Decision tree model, Got the accuracy of 84.6% by performing depth up to 15

Credit score prediction using classification models (Multi-class prediction)

This is a Premiere Project done by Team Gitlab in Hamoye Data Science Program Dec'22. Out of 5 models used on the data, Random Forest Classifier was used to further improve the prediction of characters death. With parameter tuning and few cross validation, we were able to reduce the base error by 5.42% and increase accuracy by 2,42%.

This project aims to develop a machine learning model to predict bike-sharing demand based on various factors such as weather conditions, time of day, and historical usage patterns. The dataset used for this project consists of 8760 records and 14 attributes.

End to End Machine Learning Projects Examples

Classification model to predict the probability that a customer defaults based on their monthly customer statements using the data provided by American Express.

This repository has the implementation of hyperparameter tuning techniques (GridSearchCV and RandomSearchCV) on K-Nearest Neighbour (KNN) algorithm, from scratch.

Building a plagiarism detector that examines a text file and performs binary classification labeling that file as either plagiarized or not, depending on how similar that text file is to a provided source text.

Machine Learning with Sklearn

GridSearchCV, RandomSearchCV For Model optimization and Saving/Loading the model

Implementation of Hyper-parameter tuning of ML models

Exploratory data analysis and machine learning classification models to predict employee attrition.

Use of Gradient Boosting Descision Trees for a Classification Problem

Enhancing The Performance Of Classifiers In Detecting Abnormalities In Medical Data Using Nature Inspired Optimization Techniques

This is an End-to-End Data Science Project built in order to help an International E-commerce Company to predict whether their product will be delivered on the committed Delivery Time or not