Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics
Decision_Tree_Regression I implemented the decision tree regression algorithm on Python. Unlike regular linear regression, this algorithm is used when
TensorFrames (Deprecated) Note: TensorFrames is deprecated. You can use pandas UDF instead. Experimental TensorFlow binding for Scala and Apache Spark
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.
mltrace tutorial Date: October 2021 This tutorial builds a training and testing pipeline for a toy ML prediction problem: to predict whether a passeng
MachineLearning A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts. Tested algorithms:
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-
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
Categorical Encoding Methods A set of scikit-learn-style transformers for encoding categorical variables into numeric by means of different techniques
Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po
AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast
Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time
MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.
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