Using random forest to predict the likelihood of an individual opening a bank account.
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Updated
Jul 20, 2021 - HTML
Using random forest to predict the likelihood of an individual opening a bank account.
If you run into someone on the street during a zombie apocalypse, how will you know if that's a human or a zombie? Armed with the correct classification technique, you'll be able to dodge zombies just like Jesse Eisenberg's character.
A simple perceptron implemented in R.
Build a predictive accident analysis app by loading historical accident data, preprocessing with Scikit-learn's Pipeline, training a model, and deploying using Streamlit for real-time predictions.
python deep learning classification jupyter notebook
Udacity DataScience nanodegree classification problem
Developed multiple data sets using Classification and Regression techniques to find My Airbnb NY housing price project uses given feature variables to predict housing price. I also compare my predictions to the given target variable, which is the housing price, to check if my prediction fits with the actual price.
Class Project for Data Processing and Management(Monsoon'22)
Employing several supervised algorithms to accurately model individuals' income using data collected from the 1994 U.S. Census to construct a model that accurately predicts whether an individual makes more than $50,000, This sort of task can arise in a non-profit setting, where organizations survive on donations.
Model klasyfikacyjny wykorzystujący algorytm Random Forest napisany w języku R.
"End-to-End Machine Learning Pipeline Creation Using DVC: A comprehensive MLOps solution on GitHub." This GitHub repository showcases the implementation of an end-to-end machine learning pipeline using DVC (Data Version Control) for efficient data management and MLOps practices. The pipeline covers the entire machine learning workflow.
This repository describes the implementation of Machine Learning techinques using the Statsmodels pacakge
Neste projeto de Análise de Recursos Humanos, temos como objetivo responder questões-chave sobre gestão de talentos e rotatividade de colaboradores em uma empresa fictícia.
Churn Analysis
ETL and preprocessing of data to evaluate the possibilities of creating a machine learning models to predict whether a bidding item registered in purchases from ComprasGov systems will not have interested suppliers.
Traffic Sign Classifier using Deep Learning (LeNet Architecture)
Artificial intelligence applications by Django framework (back-end) and bootstrap(front-end).
Using R Markdown for Data Analysis, Machine Learning
AI project using deep learning (CNN) to flower classification
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