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.
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 a machine learning model to predict the survival in titanic disaster.
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
Machine Learning Using Python & Sci-Kit Learn
Machine Learning for Economics (Sogang University, 2022-2)
Best practices for solving Machine Learning Multilabel Classification problems
DIY implementations of machine/deep learning models used on a variety of datasets.
Predictive machine learning model with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa.
Its purpose is to learn different classification model from the training sample set to predict the category of unknown new samples.
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 is a super basic tutorial for beginners that want to wrap their heads around fundamental concepts in machine learning
Predicting breast cancer in women in the next five years
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.
Credit Card Fraud Detection using various machine learning algorithms.
Handwritten digit recognition is the ability of a computer system to identify and process handwritten numbers. This is typically done using machine learning algorithms that are trained on a large dataset of labeled images. The goal of this project is to accurately classify the digits in order to make them easier for humans to read.
This repository provides a comprehensive overview of various machine learning concepts and their practical applications.
This is the machine learning I have done in The University of British Columbia
App to count and identify crops in a raster with machine learning