Predictive machine learning model with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa.
-
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.
Using Machine Learning to predict the likelihood of a loan default using a loan data set obtainable from Kaggle. I employed Classification for the building the machine learning models as the target variables were binary, 0 and 1 representing no default and defaulted.
This is the machine learning I have done in The University of British Columbia
This is a machine learning model to predict the survival in titanic disaster.
Helps to predict the rent of a house in indian metro cities using a machine learning model called Random Forest Regression
This is Machine Learning Beginner level Project. In this Project We can Predict fire in forest based on some features.
Projects on Machine learning using classification and regression techniques
Analysis of Contraceptive Discontinuation using machine learning
Predicting house prices in California using machine learning techniques.
This is a project where use the Random Forest Classifier and XGBoost Machine Learning Techniques to held predict what passengers survived the sinking of the Titanic.
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.
Machine Learning algorithms are implemented through homework assignments.
Machine Learning for Economics (Sogang University, 2022-2)