Supervised learning model that predicts whether an individual makes more than $50000 per year (accuracy score of 0.87) .

The goal of this project is to help a mail-order sales company in Germany to identify segments of the population that form the core customer base. These segments can then be used to direct marketing campaigns towards audiences that should bring high expected returns.

Simple API, built with FAST API, with advanced linear regression of California home prices.

Clustering Amazon review data around 6M users using Kmeans and Dbscan algorithm.

Description

This report is generated of what cryptocurrencies are available on the trading market and how they can be grouped using classification.

Testing different machine learning methods on advertising dataset. With a simple RESTAPI using flask

UCLA Computer Science Summer Institute; CS97 - Introduction to Data Science

Iniciando estudos sobre o dataset de distribuição de bolsas do ProUni

Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins

International Sports Events and Repression in Autocracies. Statistical Analysis with Python

This repository tries to predict some NBA awards with machine learning

A lung cancer decision tree is a type of machine learning model that can predict the likelihood of a patient having lung cancer based on various features such as smoking habits, age, and symptoms such as yellow fingers, anxiety, fatigue, etc.

Using ML methods, develop a data analytics-based strategy to help classify if prospective borrowers would be a risk to a bank. With the use of predictive modeling, a bank could determine whether an applicant is approved or rejected for a loan by analyzing their credit risk. (Final Group Project for CIND119)

Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.

The Crop Recommendation with Machine Learning project is designed to assist farmers and agricultural professionals in selecting the most suitable crops for their specific environmental conditions.