hyperparameter-selection

Customer Segmentation Using Unsupervised Machine Learning Algorithms

Faster machine learning training via batch size estimation

Example of an inverse problem where the aim is to reconstruct the parameters of an unknown number of weighted Gaussian function

Fast prototyping of machine learning models

Example of Neu.ro integration with NNI for hyperparameter tuning

scikit-learn-compatible hyperparameter search: BayesHalvingSearchCV (or HalvingBayesianSearchCV - Bayesian/GP) and PatternSearchCV (Hooke-Jeeves), with multi-fidelity data growth for faster tuning on large datasets

Implement Neural Network Models with different hyperparameters

Experiment with different optimizer, layers, filters, regularization for Y-Net(CNN) with CIFAR 10 and CIFAR 100 dataset

Insights into how the error varies with change in K while performing k-fold Cross Validation

Exploration of various SVMs