With this model: the amount of backlog would be reduced significantly, the amount of staff needed to do the job would be reduced drastically, the processing time would be shortened significantly and more cases of fraudulent transactions would be tracked down in a given amount of data processed - more than 40% increase in efficiency!

Over the years, the company has collected basic bank details and gathered a lot of credit-related information. The management wants to build an intelligent system to segregate the people into credit score brackets to reduce the manual efforts.. You are hired as a data scientist to build a machine learning model that can classify the credit score.

Recent times the E-commerce websites took a rapid increase in their user stats, this project is a small help for all the people out there to have a confirmation on their delivery date to avoid any issues or problems while receiving the package.

Built a Machine Learning Supervised classification algorithm, for predicting the risk of cardiovascualar disease withing coming 10 years by analyzing Patients medical History.

Ensemble multi-class classifiers on business license status data.

Employee Churn Prediction for a Kaggle Data Contest

ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.

Deep Learning vs Tranditional ML methods for TB Drug Resistance prediction from Genomic data

Classification problem to predict flight delay using: Logistic Regression, Decision Tree, Random Forest, AdaBoost, Neural Network

Application to predict future occurrence of heart attack in patients on the basis of test reports

This GitHub repository contains a collection of machine learning implementations and evaluations. It includes code for ensemble learning, decision trees, AdaBoost, logistic regression, and K-means clustering. Each section focuses on a specific algorithm or technique and provides code examples for training models, making predictions, and evaluating

Program to predict whether a person will suffer a stroke in the near future or not with help of python

This repository contains the dataset and code for Absenteeism analysis. Many algorithms like RandomForestClassifier, SVC, AdaBoost etc.. are employed. The final model is selected based on accuracy obtained after hyper-parameter tuning the models

A Water Potability Model

Using the above system, farmers can be guided in the choice of crops to be grown by predicting the suitable ones for a given region by incorporating supervised ML algorithms.

This repository contains code for a machine learning project focused on predicting the likelihood of a person having diabetes. The project includes the implementation of various classification models and an Artificial Neural Network (ANN) for classification.

Meu 8 miniprojeto em python em que faço o uso de modelos de classificação para predição da sobrevivência ou não no desastre do titanic

Create an algorithmic trading bot that learns and adapts to new data and evolving markets.

This project aims to build a model that can predict if customer is going to purchase a car or no