Popular GitHub Repositories for Cross Validation

?Hyperparameter optimization for machine learning pipelines ?

SuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.

Machine learning toolkits with Python

Resampling Tools for Time Series Forecasting with Modeltime

Solve complex real-life problems with the simplicity of Keras

Aims at attributing the big-five personality traits to authors of essays by analyzing their works.

CNN text classification using keras

This repo contains examples of binary classification with ANN and hyper-parameter tuning with grid search.

Predicting next year's GDP using ML (Python)

"Evaluation procedures for forecasting with spatio-temporal data" -- ECML 2018

FastML Framework is a python library that allows to build effective Machine Learning solutions using luigi pipelines.

Implied volatility is a key aspect when it comes to derivatives pricing. With the growing influence of machine learning in finance, I have investigated the use of LSTMs to forecast 1-day forward Implied Volatility.

Building a model which can predict the number of online 'shares' an article will get based on a set of variables attached to it. (Python)

Data Analytics and apply machine learning algorithms to predict the outlet sales production.

State of the art prediction of mosquito hotspots and virus presence using machine learning and deep learning

This repository contains a Jupyter Notebook demonstrating a practical example of data science and machine learning for heart disease classification.

Prediction of stock market time series

A time slicer for training and testing temporally correlated Machine Learning models.

Files for compiling my presentation about H2O.ai.

This repository contains the code, documentation, and datasets for a comprehensive exploration of machine learning techniques to address class imbalance. The project investigates the impact of various methods, like ADASYN, KMeansSMOTE, and Deep Learning Generator, on classification performance while effectively demonstrating benefits of pipelining.