ICML 2018: "Adversarial Time-to-Event Modeling"

[ICLR 2022] Graph-Relational Domain Adaptation

CSE 575 Statistical Machine Learning

Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests for classification of Malaria Cells

machine learning is a combination of statistics,computer science and mathematics. It uses a lot of statistical tool and mainly a lot of interpretation terms are adapt from statistics .So here I will add little but important concepts of statistics in ML.

Analyzing the binary gender difference in lead roles using statistical machine learning

TTIC Statistical Machine Learning

Conversational Lexical Affect Recognition Kit

PyTorch implementation of 'Concrete Dropout'

IEEE TNNLS 2020: "Calibration and Uncertainty in Neural Time-to-Event Modeling"

This repository contains assignments solutions for one of my postgraduate subjects of COMP SCI 7314 - Introduction to Statistical Machine Learning. The programming language is Python.

Code for the paper: LogGENE, A Smooth alternative for the Check Loss

The Flight Price Prediction project uses machine learning to forecast flight ticket prices based on historical data. Hosted on Streamlit Community Cloud and deployed via Streamlit, this application allows users to input flight details such as departure and arrival airports, travel dates, and class to receive accurate price predictions.

Statistical Machine Learning coursework (Sharif University of technology)

Building a data exploration application.

Building an application for pneumonia detection from X-ray images

Essential files for pac-bayes-tree

Học máy thống kê

The goal of this project is to implement a graph label propagation method to study and classify image data. The method has the particularity that it combines well with other classifiers to achieve enhanced performance.

The Muffin vs Chihuahua NN assignment for the Statistical Methods for ML course of UNIMi.