Predictive machine learning model with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa.
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Updated
Mar 17, 2023 - Python
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Predictive machine learning model with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa.
This Projects creates a model that predicts Google Play Store Apps Rating based on parameters like No. of Installs, reviews, size, category , genres etc. It compares several classification model like Xgboost(booster ensembler), Random Forest(bagger ensembler), Logistic regression, Support Vector Machine(SVC) and Bayesian Classifier.
This repository for machine learning projects learned from ineuron.ai uploaded along with the resources.
A curated list of my machine learning projects. Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence.
This is the machine learning I have done in The University of British Columbia
Analysis of Contraceptive Discontinuation using machine learning
Predicting house prices in California using machine learning techniques.
The goal of this project is to obtain a classifier that can automatically classify environmental sounds according to their category. This can be implemented on both transport vehicles and wearable devices to improve road safety.
This repo contains regression and classification supervised Machine Learning projects.
Classification for Beginners.
Leaf Buster AI is a machine learning project developed during the HackMerced VIII hackathon with the goal of the project being to help farmers identify and classify diseases in their crops using computer vision and artificial intelligence.
Predicting breast cancer in women in the next five years
Football Prediction Model
In this project, five different machine learning (ML) models are trained and compared in term of predicting the early-stage diabetes. A data collected in hospital Frankfurt, Germany containing 2000 patients’ information have been used in this study. RF, NB, SVM, KNN, and LR are the five models used for predicting the diabetes.
Practical Approach to AI (example testing)
App to count and identify crops in a raster with machine learning
This project uses machine learning classifier algorithms to predict whether the patient is suffering from cancer or not.