hyperparameters-optimization

awslabs/Renate

Library for automatic retraining and continual learning

guillaume-chevalier/Hyperopt-Keras-CNN-CIFAR-100

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

dc-aichara/DS-ML-Public

Python Scripts and Jupyter Notebooks

reiase/hyperparameter

Hyperparameter, Make configurable AI applications.Build for Python hackers.

yassineAlouini/hyperparameters-optimization

The accompanying repo for the hyperparameters optimization bdx meetup talk, blog post and webinar

IFFranciscoME/Genetic-Finance

Implementations of Genetic Methods for Financial Machine Learning Applications

angusfung/pbt-gan

Applying Population Based Training on Generative Adversarial Networks.

giuliots95/Time_series_forecast_with_LSTM_network

This repository contains the implementation of a recurrent neural network (LSTM from keras library) with the purpose of forecasting target time series, given the targets historical records and covariates. The project uses a toy data set, while focusing on the data transformation tasks (pandas dataframes to 3D numpy arrays required by recurrent networks) and on the hyperparameters tuning tasks, taking advantage of keras_tuner package.

JLX0/llm-automl

Automate machine learning tasks at the code level with LLMs and autoML | Based on the TMLR paper "Large Language Models Synergize with Automated Machine Learning"

aquemy/DOLAP_2019_supplementary_material

Supplementary material for DOLAP 2019 submission

aurelienmorgan/french_text_sentiment

Sentiment Analysis in texts written in French language using Tensorflow/Keras (and using XGBoost for hyperparameters optimization)

Moddy2024/Cat-or-Dog-Image-Classification

I have trained two different CNN models for binary image classification to see which architecture has better accuracy, takes less time in training, how hyperparamters affect training and how many epochs do each of them need. I achieved 96% accuracy on the best model.

Hands-On-Fraud-Analytics/Chapter-18-Classification-Techniques-For-Fraud-Detection

Classification-Techniques-For-Fraud-Detection

jw-mcgrath/HyperYAML

A library to build and run HyperOpt Hyper Parameter Optimization Schemes

marvinzh/cma_es

a CMA-ES based hyperparameter optimization tool for NMT.

mekhod/boston_housing

An exploratory data analysis is performed and a regression model is used to predict house values. The prediction performance is optimized after tuning the model hyper-parameters to minimize bias/variance errors.

igoracmorais/tuning_hyperparameters

Diferentes processos que podem ser usados para encontrar os hyperparâmetros ótimos em aplicações de Inteligência Artificial.

PFalkowski/SimpleRegression