This machine learning model was developed for "House Prices - Advanced Regression Techniques" competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
Cross validation phases are given as comment with their results. They can be uncommented and tested again.
The project's goal is to show a real world application of image segmentation using k means algorithm
This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses
House-Price-Prediction-Using-Linear-Regression The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal. Link of Datase
Winning solution for the Galaxy Challenge on Kaggle
Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
Azure MLOps (v2) solution accelerator Welcome to the MLOps (v2) solution accelerator repository! This project is intended to serve as the starting poi
Machine Learning University: Accelerated Natural Language Processing Class This repository contains slides, notebooks and datasets for the Machine Lea
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p
Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas
Nixtla Nixtla is an open-source time series forecasting library. We are helping data scientists and developers to have access to open source state-of-
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
mummify is a version control tool for machine learning. It's simple, fast, and designed for model prototyping.
Educational python for Neural Networks, written in pure Python/NumPy.
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and t
tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p
This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d
Katana ML Skipper This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable
Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj
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