Data analysis, visualization, classification

A Machine Learning project

This project uses data from Olist - a Brazilian e-commerce platform to predict customer's review scores. The full Python code is presented in 3 steps: data preprocessing, EDA & modeling, followed by a Tableau Dashboard on customer ratings.

Flight ticket prices can be something hard to guess, today we might see a price, check out the price of the same flight tomorrow, it will be a different story. This is the reason why flight prices are quiet unpredictable. Data consisting of several details and prices of flight tickets for various airlines between the months of March and June of …

machine learning (logistic regression and other algorithm )

Data Science and Machine Learning using Python and R

This is a prediction of the duration of taxi trips in new york. The main work is based on the dataset adding a weather datasaet and many other features (rush hours, weekend days, speed, etc...). You can check my medium publication where I explain all the work done. MEDIUM: https://medium.com/cuny-csi-mth513/new-york-city-taxi-trip-duration-predi…

AI

This project focuses on predicting house prices in Miami using regression techniques. By exploring and analyzing the data, performing feature selection and scaling, trying out different models, and tuning hyperparameters, we aim to develop an accurate model for predicting house prices.

Machine learning project for cardiovascular risk prediction. The goal is to predict whether the patient has a 10-year risk of future coronary heart disease (CHD)

Diabetes Health Indicator Dataset analysis with R

homesite kaggle

Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook

In this project I used different regression algorithms to predict sales of stores. I used Kaggles free GPUs and Datasets in this competition. Those different algorithms include random forrest, decision tree, xgboost, K Nearest Neighbour and so on. Initially I used feature engineering to get my data into the best shape.

A Repository for handling different complex machine learning algorithms like boosting etc. This repository contains/will contain all the important algorithms implemented on real data. The helper functions defined will prevent from writing complex codes and will help us realize our goal faster.

The diamonds price prediction with linear regression models.

Comparative Analysis of Machine Learning Models for Predicting Smart Grid Stability