Tennis Player strength Analysis using Machine Learning
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Updated
Jun 24, 2019 - Jupyter Notebook
Tennis Player strength Analysis using Machine Learning
Ensembles method implemented in C#
Cross-Pollinated Deep Ensembles (NeurIPS Europe Meetup on Bayesian Deep Learning 2020)
Repository for Reproducibility for the Paper: "CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure".
Off-the-Shelf Ensemble Systems
Text Sentiment Analysis using Ensembles
Connecting the Sustainable Development Goals with climate change and the energy transition
Utilities for comparing paleoclimate reconstruction ensembles
Predictive Analysis of detecting signal emitting Source
Repositorio que contiene los scripts y explicaciones en R para elaborar un estudio del data set Titanic por medio de un proceso de preprocesado de datos, regresión logística para la selección de variables y árboles de decisión. Prácticas de la asignatura Tratamiento Inteligente de Datos.
CS760: Machine Learning
We provide two notebooks that enable users to explore and experiment with some BDL techniques as Ensembles, MC Dropout and Laplace Approximation. In this way, they allow you to intuitively visualize the main differences among them in a Simulated Dataset and Boston Dataset.
This is where I'll post my machine learning templates that I've created
R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.
The PyTorch framework developed to enable my MSci thesis project titled: "Evaluating Uncertainty Estimation Methods For Deep Neural Network’s In Inverse Reinforcement Learning"
Tree-based survival analysis from scratch
Repository for Reproducibility for the Paper: "Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML"
Tool to analyze two-photon calcium imaging videos, extract neuronal activity, and identify neuronal ensembles (ONsembles and OFFsembles).
Decision and Ensemble methods implemented in C#
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