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.
A benchmark of data-centric tasks from across the machine learning lifecycle.
Seldon Core: Blazing Fast, Industry-Ready ML An open source platform to deploy your machine learning models on Kubernetes at massive scale. Overview S
This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm
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
Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid
ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from
Submit it! What is submitit? Submitit is a lightweight tool for submitting Python functions for computation within a Slurm cluster. It basically wraps
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt
Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.
PosteriorStacker Combines Bayesian analyses from many datasets. Introduction Method Tutorial Output plot and files Introduction Fitting a model to a d
R-Solver A Python tools for deriving R-Type adaptors for Wave Digital Filters. This code is not quite production-ready. If you are interested in contr
MachineLearning A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts. Tested algorithms:
pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
forest-confidence-interval: Confidence intervals for Forest algorithms Forest algorithms are powerful ensemble methods for classification and regressi
Machine Learning Notebooks, 3rd edition This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code
CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning
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