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.
Machine Learning Loot Crate 💻 🧰 🔴 Welcome contributors! As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Cra
Databricks Certification Spark Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
Educational python for Neural Networks, written in pure Python/NumPy.
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill This is a port of the amazing openskill.js package
Diabetes Prediction with Logistic Regression Exploratory Data Analysis Data Preprocessing Model & Prediction Model Evaluation Model Validation: Holdou
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Implemented four supervised learning Machine Learning algorithms from an algorithmic family called Classification and Regression Trees (CARTs), details see README_Report.
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark
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Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
Python Research Framework
Python package for probability density function fitting of univariate distributions of non-censored data
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C
The Simpsons and Machine Learning: What makes an Episode Great? Check out my Medium article on this! PROBLEM: The Simpsons has had a decline in qualit
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