Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers.
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th
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.
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.
Demand-Forecasting Business Problem A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.
PosteriorStacker Combines Bayesian analyses from many datasets. Introduction Method Tutorial Output plot and files Introduction Fitting a model to a d
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
Tribuo - A Java prediction library (v4.1) Tribuo is a machine learning library in Java that provides multi-class classification, regression, clusterin
SDK: Overview of the Kubeflow pipelines service Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on
Cohort-Intelligence-for-Mathematical-Functions About Cohort Intelligence : Cohort Intelligence ( CI ) is an optimization technique. It attempts to mod
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
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Hover Example Apps (works out-of-the-box on Binder) This repository demonstrates the usage of hover to understand and supervise a machine learning tas
Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with
PROTEIN-EXPRESSION-ANALYSIS-FOR-DOWN-SYNDROME Down syndrome (DS) is a chromosomal disorder where organisms have an extra chromosome 21, sometimes know
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
Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.
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