Testing several hyperparameter optimization techniques.
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Updated
Jul 20, 2020 - Python
Testing several hyperparameter optimization techniques.
I implement I-AutoRec (an autoencoder framework for collaborative filtering b) with Keras and tuned hyperparameters of this model using a validation set.
Sweep through ranges of command line hyperparameters to create testcases for multiple corners
Simple logging wrapper for model hyperparameters from gensim.d2v, sklearn and keras.
Example of Neu.ro integration with NNI for hyperparameter tuning
A Hyperparameter Tuning algorithm.
Hyperparameter search algorithm
Bayesian hyperparameters optimization for neural networks
Simple parameter space creation library for python
Automatically create a config of hyper-parameters from global variables
Bachelor Degree Project in Information Technology
A design space exploration tool for deep neural architectures
Fast prototyping of machine learning models
Large Scale Machine/Deep Learning library for Python
Python GUI and PyTorch based backend to train a DNN or CNN on the MNIST handwriting dataset, classify digits the user draws in the GUI, and save hyperparameter info for a MATLAB graph.
In this research project, we aim to create an environment to gather structured data about machine learning experiments in order to analyze data and algorithmich dependencies.
Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.
Detailed industry specific framework to solve Machine Learning Problem
Yet Another Config Manager for MAchine Learning (yacmmal) is a package to automatically load config files for machine learning projects.
A python library for managing Hyperparameters
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