"Excited to share my latest project on LinkedIn: a crop yield prediction ML model deployed with Streamlit! 🌱 Leveraging the power of Stochastic Gradient Descent regression(SGD) algorithm, this tech-driven solution boasts an impressive 94% accuracy on both training and testing data.

Project to predict retention of students in a study program up-to and beyond semester 6 based on scores, socio-economic & demography factors (like debt, gender, religion and race), transferred credits, family fee contributions, academic background, phone and email habits.

machine learning a to z udemy course

Supervised (ML) Regression - NYC Taxi Trip Time Prediction, based on 2016 NYC Yellow Cab published by Taxi & Limousine Commission (TLC).

This project focuses on modelling industrial copper data using Python and various libraries such as pandas, numpy, scikit-learn

A linear regression project using e-commerce data to predict customer spending and determine whether a mobile app or website drives more revenue. Built with Python, pandas, seaborn, and scikit-learn, this analysis helps guide digital strategy by identifying key user behavior patterns tied to yearly amount spent

A simple R program that implements a very basic Polynomial Regression on a small data set. Because these data set don't have liner relationship between independent variable and dependent variable. so if we use the liner model then well get very High error. so in these example w'll compare both the model and select which one is best.

Machine learning

This where I will upload all my machine learning projects and samples

EDA, Regression Analysis , Classification & Non-Parametric inference Problems

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

Forecasting stock market and simulating buy/sell stock market using 5 classifications and 5 regression models, as well as 5 data sets.

Machine learning projects in ecommerce and retail domain

What's the Weather Like?

Hamoye Data Science Cohort 2021

The idea behind this Intro to Machine Learning Guide was to initially create a list of resources to provide to my students. This eventually morphed into a comprehensive guide that will eventually cover everything from Linear Regression to Neural Networks

Análise de um estudo de coorte sobre pessoas com câncer de tireóide. Realização de análise descritiva, aplicação de testes estatísticos e desenvolvimento de um modelo de regressão logístico com desfecho remissão do câncer.

Predicting automobile prices using machine learning and data visualization. This project leverages XGBoost and Python libraries to achieve an R² score of 0.94, with clean preprocessing, insightful visualizations, and reproducible code.