This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.
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Updated
Sep 29, 2022 - Jupyter Notebook
This project is about predictive maintenance with machine learning. It's a final project of my Computer Science AP degree.
The aim of this project to retail analysis with Walmart data.
Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.
Over 10 years of hourly energy consumption data from PJM in Megawatts
Projet-PI-4DS2
This repository provides an online certification program in Data Science and Machine Learning offered by IBM and Coursera. The program covers topics such as data science methodology, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. The courses are hands-on and conducted on the IBM Cloud,
A ready to use template for the CRISP-DM data science workflow
The current project provides a Machine Learning trained model that is able to classify the trait with maximum value of the Big Five Personality Test, given the answers of this one.
Predict if SpaceX Falcon 9 first stage will land successfully after rocket launches.
Graduation project categorizes popular search phrases using Python and Spark and presents them on a website to inspire creators.
Forecast sales using store, promotion, and competitor data
Materials accompanying the Saxion AI Training sessions organised in 2021.
CRISP-DM Project of Udacity Data Scientist Nanodegree
This is a sample for a Data Mining project following CRISP-DM methodology
Walmart Store Sales Forecasting
Data processing, Model creation and App deployment of Vesper Commit Severity Predictor. Trained with data from the Technical Debt Dataset.
Bank Marketing Prediction. Binary Classsification
Data mining project, about the rain situation in Australia
Este projeto permitirá que a rede de supermercados compreenda melhor as interações entre clientes e funcionários, identificando oportunidades de aprimoramento no atendimento. Aumentando a satisfação do cliente e melhorando a eficiência
Building Personalised Recommendations with Machine Learning for Financial Services Marketing: A Collaborative Filtering Approach
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