hyperparameter-optimization

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Here are 26 public repositories matching this topic...

seba-1511 / randopt

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Streamlined machine learning experiment management.

visualization hyperparameters hyperparameter-optimization experiments

Updated Apr 27, 2020
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jakob-r / mlrHyperopt

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Easy Hyper Parameter Optimization with mlr and mlrMBO.

machine-learning r optimization hyperparameter-optimization r-package mlr tuning-parameters learners

Updated Jan 5, 2022
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szilard / GBM-tune

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Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions

machine-learning hyperparameter-optimization gbm gradient-boosting-machine overfitting

Updated Sep 11, 2017
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Neural is a domain-specific language (DSL) designed for defining, training, debugging, and deploying neural networks. With declarative syntax, cross-framework support, and built-in execution tracing (NeuralDbg), it simplifies deep learning development.

visualization data-science machine-learning automation visual-programming-language tensorflow dsl data-visualization pytorch neural-networks hyperparameter-optimization diagrams lark neural-architecture-search onnx nocode neural-networks-and-deep-learning neural-networks-from-scratch llms

Updated Jun 23, 2025
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ChaitanyaC22 / Udacity-AWS-MLE-ND-Project1-Bike-Sharing-Demand-with-AutoGluon

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This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

python data-science machine-learning deep-learning exploratory-data-analysis machine-learning-algorithms jupyter-notebook hyperparameter-optimization amazon-web-services boosting-algorithms feature-engineering model-evaluation automl stacking model-building ensemble-methods autogluon

Updated Jan 24, 2023
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ahmedshahriar / Customer-Churn-Prediction

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Extensive EDA of the IBM telco customer churn dataset, implemented various statistical hypotheses tests and Performed single-level Stacking Ensemble and tuned hyperparameters using Optuna.

kaggle xgboost hyperparameter-optimization scipy lightgbm binary-classification ensemble-classifier catboost pandas-python classification-models optuna customer-churn-prediction stacking-ensemble

Updated Nov 9, 2021
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nitishkthakur / automlib

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AutoML Python package with ML models with builtin Hyperparameter Optimization and easy to use API.

python learning machine-learning optimization machine machine-learning-algorithms ml python3 hyperparameter-optimization machinelearning python-3 tune optimization-algorithms particle-swarm-optimization automl automl-api

Updated Oct 24, 2019
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arnaudhillen / coursera-deep-learning-specialization

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The jupyter notebooks of the deep learning specialization by deeplearning.ai

machine-learning deep-learning coursera assignment artificial-intelligence neural-networks hyperparameter-optimization artificial-neural-networks convolutional-neural-networks hyperparameter-tuning sequence-models structuring andrew-ng-course

Updated Aug 30, 2018
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Purushothaman-natarajan / Yoga_Pose-Image-Classification

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This repository offers a robust solution for multilabel image classification. Utilizing advanced neural networks like VGG16, VGG19, ResNet50, InceptionV3, DenseNet121, and MobileNetV2, the project achieves precise classification across 107 diverse categories.

python data-science machine-learning deep-neural-networks computer-vision tensorflow image-processing hyperparameter-optimization image-classification convolutional-neural-networks transfer-learning hyperparameter-tuning multilabel-classification model-optimization

Updated Jul 23, 2024
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makeyourownmaker / BayesianProphet

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Bayesian optimisation of prophet temperature model parameters with daily and yearly seasonalities plus extra regressors

python weather time-series jupyter temperature forecast daily hyperparameter-optimization multivariate bayesian-optimization prophet yearly multi-step regressors nowcast multi-seasonal

Updated Apr 25, 2021
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eliottkalfon / evolution_opt

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Evolution-inspired optimisation algorithms

machine-learning genetic-algorithm hyperparameter-optimization evolutionary-algorithms automl

Updated Feb 19, 2021
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daksh-intwala / House-Price-Prediction--Regression-Anaylsis

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A simple regression analysis of house prices in USA with 11 features selected on MECE Framework

error-handling hyperparameter-optimization standardization bayesian-data-analysis hyperparameter-tuning ols-regression bias-variance normalization minmax-algorithm lasso-regression regression-analysis

Updated Sep 9, 2021
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nursena8 / BankCustomerProject

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Machine learning classification model with streamlit deployment.

machine-learning scikit-learn hyperparameter-optimization gbm streamlit evidentlyai

Updated Feb 16, 2024
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chrinide / h2o-hyperopt

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Library for integrated use of H2O with Hyperopt

machine-learning deep-learning h2o hyperparameter-optimization

Updated Aug 12, 2016
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MvMukesh / EmployesEarning-DeepAnalysis_Prediction

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What important conclusion a company and an employee can take out of Analysis and Predicting Salary

machine-learning random-forest linear-regression machine-learning-algorithms python3 xgboost hyperparameter-optimization metric-learning adaboost decision-tree hyperparameter-tuning gridsearchcv chisquare-test chi2-distance randomizedsearchcv anova-test chi2-contingency kneighborsregressor lightgra

Updated Feb 4, 2023
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desaimilin / NNDL-2020

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This repository focuses on the Neural Networks and deep learning. It is a workbook you can refer it for a reference. I'll Include following content here: Neurons, perceptrons, weight and biases, learning rate, activation form, hyper parameters, RNN, CNN and other popular concepts.

deep-learning neural-network hyperparameter-optimization neurons perceptron hyperparameter-tuning rnn-tensorflow learning-rate cnn-keras