Sign Language Digit Classification
-
Updated
Jun 3, 2018 - R
Sign Language Digit Classification
Binary Classification Models On Skin Dataset
Probabilistic graphical models home works (MVA - ENS Cachan)
Introduction to Data Mining
Introduction to Statistical Learning with Application in R[This repo converts the lab solutions and exercise in python]
A synchronous Kernels-only competition
Pseudo-Inverse, Gradient-Stochastic-Steepest Descent, Logistic Regression and LDA-QDA
The projects are part of the graduate-level course CSE-574 : Introduction to Machine Learning [Spring 2019 @ UB_SUNY] . . . Course Instructor : Mingchen Gao (https://cse.buffalo.edu/~mgao8/)
This repository contains Jupyter Notebook file containing the code to compare different sklearn classifiers on a dataset. Then it saves the output .png results in the working folder.
Analysis of the Avila bible dataset from the UCI repository using several machine learning algorithms.
Heart Failure Prediction for Harvard University Professional Certificate in Data Science Capstone Project, 2nd Capstone Project using R programming
Statistical machine learning
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Here, the aim is to analyze the dataset and detect the fradulent transactions.
2019.12.12 개인 프로젝트. 직원의 퇴사를 예측하고 퇴사 이유 및 해결방안 제시
Linear Discriminant Analysis
Personal reimplementation of some ML algorithms for learning purposes
A simple data parser to aid in the process of Qualitative Data Analysis with multimodal data
statistical learning course by dr. Mohammad zade at Sharif Uni. of Tech
Working through all the exercises for An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.
Add a description, image, and links to the qda topic page so that developers can more easily learn about it.
To associate your repository with the qda topic, visit your repo's landing page and select "manage topics."