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.

Essential files for pac-bayes-tree

Học máy thống kê

This project aim to build a recommendation system for Steam games. It utilizes different machine learning models including LSTM, ResNet, and NCF (Neural Collaborative Filtering) to predict and recommend games based on user data and interactions.

A supervised machine learning project where I develop a number of models to classify an individual's income level using census data.

Project in the course TDDE16 - Text Mining at Linköping University

Developed and deployed a predictive model for estimating housing prices using the Ames Housing Dataset. Utilized advanced regression techniques and feature engineering to achieve high accuracy. Successfully implemented the model as an interactive web application on Streamlit, enabling real-time predictions.

Statistical Machine Learning coursework (Sharif University of technology)

Building a data exploration application.

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.

A comprehensive machine learning analysis of hotel data scraped from Booking.com in Ho Chi Minh City, Vietnam. This project leverages various ML techniques to extract insights from hotel reviews, images, and metadata to provide actionable intelligence for the hospitality industry.

Assignments of lecture

Authorship attribution is a task to identify the author of a given document. Our task is to come up with test predictions for an authorship attribution problem given a training set and test inputs.

Attempting to make Statistics for Machine Learning easy to learn and understand

Building an application for pneumonia detection from X-ray images

Development and Evaluation of Neural Net Sensitivity-Based Pruning Algorithms Using Statistical Inference

Python implementation of Bayesian Online Changepoint Detection, Adams, R. P., & MacKay, D. J. C. (2007)

Loss J's statistical machine learning course. 🚀

My assignments/project for MATH5470 Statistical Machine Learning