The ability to predict prices and features affecting the appraisal of property can be a powerful tool in such a cash intensive market for a lessor. Additionally, a predictor that forecasts the number of reviews a specific listing will get may be helpful in examining elements that affect a property's popularity.

This project analyzes employee attrition data to uncover key factors, predict turnover, and develop strategies for retention, ultimately enhancing organizational stability and performance.

Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets

This project aims to predict diabetes using data mining techniques and various machine learning models. We utilized a diabetes dataset to train and evaluate multiple learning models.

This project aims to forecast brewery sales using PySpark and deploy the solution on Google Cloud Platform (GCP).

This is a machine learning (Image Classifier) web app, that lets the user upload an image of a sports celebrity (Lionel Messi, Maria Sharapova, Roger Federer, Serena Williams, Virat Kohli) and predicts whose image is uploaded.

The objective of this project is to apply my knowledge of data science and machine learning to create a house price prediction model in a well documented fashion

sklearn search grid for model selection and more

This app predicts whether you have Diabetes or not, based on a machine learning model trained on the dataset provided by the National Institute of Diabetes and Digestive and Kidney Diseases.

Here I write some code for ML and NN with pain

Exploring the intersection of supervised machine learning algorithms and weather data to drive ClimateWins forward. (CF student project)

Pipeline creation using Pipeline and make_pipeline along with ColumnTransformer and an Estimator

This project aims to aims to predict the customer churn (likelihood of a customer leaving the company) for a telecom company using a variety of ML classification algorithms.

Aquí compartiré y documentaré mi aprendizaje en el análisis predictivo utilizando ML y prácticas de Python. Variando desde simples ejercicios hasta proyectos prácticos. Cada proyecto incluye archivos de soporte y notebooks con código y análisis y las prácticas sus enunciados comentado al inicio.

Python machine learning classification algorithm that calculates the percentage of spam in a dataset of thousands of emails.

The primary aim of this project is to accurately identify individuals at risk of diabetes based on different features.

Analyzing Fater company's diaper market potential and enhancing revenue estimation for Naples stores: A Socio-Demographic, Territorial, and Points of Interest Perspective

Open University Learning Analytics Dataset (OULAD) analysis exercise

A Streamlit ML app for flight price prediction. This one project involves concepts like EDA, Linear, Lasso & Ridge Regression, Kfold, Hyper Parameter Tuning & GridSearchCV. I am constantly building a rich repository of all the information I have on a particular topic as part of my machine learning practice. Very Helpful for ML beginners.