Solution of the Titanic Kaggle competition
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Updated
Feb 7, 2021 - Jupyter Notebook
Solution of the Titanic Kaggle competition
A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning
hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.
Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'
Aims at attributing the big-five personality traits to authors of essays by analyzing their works.
Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets
Analysis of Terry Stops in Seattle
A lightweight tool to manage and track your large scale machine leaning experiments
Lightweight HyperParameter Optimizer
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Build a machine learning model to predict if a credit card application will get approved.
This project implements famous MAB algorithms and evaluates them on the basis of their performance - EpsilonGreedy, UCB, BetaThompson, LinUCB, LinThompson.
Using supervised learning on Lending Club loan data to predict default and / or bad loans
Yandex Practicum Data Science project
Testing several hyperparameter optimization techniques.
Deep Q Learning (DQN) neural net to optimize a lunar lander control policy using OpenAI Gym environment.
Implementation of various algorithms on scikit-learn's Toy Datasets.
Prediction of forest cover type in Python.
Comparison of Models using NASA Kepler data
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