Topic: regularization-methods Goto Github
Some thing interesting about regularization-methods
Some thing interesting about regularization-methods
regularization-methods,Using encoder-decoder neural networks to learn representations of personal walking style, and generating person-specific gait for desired activities.
User: abs711
regularization-methods,Iris plants dataset
User: adityashah-iitp
regularization-methods,A quantitative measure of disease progression one year after baseline
User: adityashah-iitp
regularization-methods,Analyzing car accident fatalities to pave the way for preventative measures and safer transportation using Statistical and Machine Learning algorithms
User: alecruces
regularization-methods,The objective is to build various classification models, tune them and find the best one that will help identify failures so that the generator could be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.
User: alef-s
Home Page: https://eportfolio.mygreatlearning.com/vanessa-florez
regularization-methods,Adding noise as regularization method to reduce overffiting in neural networks
User: alejandrods
Home Page: https://towardsdatascience.com/noise-its-not-always-annoying-1bd5f0f240f
regularization-methods,Implementation of optimization and regularization algorithms in deep neural networks from scratch
User: aliyzd95
regularization-methods,Through this project we will try to understand CutMix by implementing it on a simple problem of cat-vs-dog classification.
User: ar8372
regularization-methods,This is Collection of Regularization Deep learning techniques with code and paper
User: ashishpatel26
regularization-methods,In linear regression, regularization is a process of making the model more regular or simpler by shrinking the model coefficient to be closer to zero or absolute, ultimately to address over fitting.
User: camythaocta
regularization-methods,Notebooks developed in Mathematica for my Ph.D. thesis and other resources
User: carolinaperdomo
regularization-methods,Using over 5,800 images of chest radiographs, I utilized machine learning and neural networks to predict when pneumonia is present. The best model was able to predict over 80% accuracy on the test data with a false negative rate that was less than 3%.
User: cassnutt
regularization-methods,
Organization: chandar-lab
regularization-methods,A school bootcamp for hands on learning of Machine Learning
User: cnstll
regularization-methods,Constructing a linear regression model which may help us predict the happiness score in the 155 countries.
User: dataengel
regularization-methods,Using deep learning to predict whether students can correctly answer diagnostic questions
User: devanshkhare1705
regularization-methods,Functional Group Bridge for Simultaneous Regression and Support Estimation (https://arxiv.org/abs/2006.10163)
User: dipterix
regularization-methods,A vast assortment of class regularization images in sets of 1500
User: distraict
regularization-methods,Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.
User: dizam92
regularization-methods,Repository with some implementations of algorithms used in Numerical Analysis. From the solution of determined and overdeterminded systems to regularization and non-linear least square problems.
User: ez77
regularization-methods,Machine Learning and Data Mining Projects (2022-2023)
User: faresgh1997
regularization-methods,Regularized Levenberg-Marquardt algorithm for nonlinear regression on small size datasets
User: flowel1
regularization-methods,Python source code for EMNLP 2020 Findings paper: "Domain Adversarial Fine-Tuning as an Effective Regularizer".
User: georgevern
regularization-methods,Code and Data sets for the EMNLP-2021-Findings Paper "ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection"
User: inimah
Home Page: https://aclanthology.org/2021.findings-emnlp.138
regularization-methods,All my Machine Learning Projects from A to Z in (Python & R)
User: joycechidi
regularization-methods,Conducted advanced research on unsupervised image segmentation using Lipschitz regularity constraints
User: juliusgraf
regularization-methods,This work attempts to generalize a stock forecasting neural network using Bayesian regularization so that predictions can be performed without an overfitted model, considering the highly volatile market these days.
User: kaushikpalani
regularization-methods,Ridge Regression Work
User: kevjh18
regularization-methods,Here, we implement regularized linear regression to predict the amount of water flowing out of a dam using the change of water level in a reservoir. In the next half, we go through some diagnostics of debugging learning algorithms and examine the effects of bias v.s. variance.
User: kk289
regularization-methods,Stable-Baselines Implementation of MixReg regularization technique for PPO2
User: kristofpusztai
regularization-methods,Sparse Gaussian graphical models with Sorted L-One Penalized Estimation
User: krystynagrzesiak
Home Page: https://statsimuwr.github.io/gslope
regularization-methods,Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng
User: lironmiz
Home Page: https://www.coursera.org/specializations/machine-learning-introduction#howItWorks
regularization-methods,Pre-Rendered Regularization Images fou use with fine-tuning, especially for the current implementation of "Dreambooth"
User: luehrsen
regularization-methods,Code for the paper "Module-based regularization improves Gaussian graphical models when observing noisy data"
User: magnusneuman
regularization-methods,Machine Learning Projects
User: mbidu
Home Page: https://github.com/mbidu
regularization-methods,A Julia package to perform Tikhonov regularization for small to moderate size problems.
User: mdpetters
Home Page: https://mdpetters.github.io/RegularizationTools.jl/stable/
regularization-methods,All about machine learning
User: nvsyashwanth
Home Page: https://nvsyashwanth.github.io/machinelearningmaster/
regularization-methods,Supervised learning and unsupervised in R, with a focus on regression and classification methods.
User: paulinealvarado
regularization-methods,Digital Image Reconstruction
User: richardd3ng
regularization-methods,Supplementary code for the paper "Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks" - an accepted paper of LOD2019
User: rpatrik96
regularization-methods,linear regression
User: saibharath2
regularization-methods,Classification Using Logistic Regression by Making a Neural Network Model. This project also includes comparison of Model performance when different regularization techniques are used
User: saisriramyerubandi
regularization-methods,Implementation of all basic algorithms needed in Deep Learning
User: sauriii98
regularization-methods,the implementation of a multilayer perceptron
User: shimazadeh
regularization-methods,Notebooks of programming assignments of Improving Deep Neural Networks course of deeplearning.ai on coursera in August-2019
User: subangkar
regularization-methods,Machine Learning Course Topic wise Assignments and Projects
User: sushmitha-93
regularization-methods,Activities include Python basics, linear and logistic regression, cross-validation, tree-based methods, SVMs, deep learning, survival analysis, unsupervised learning, and multiple testing.
User: thecodingmooseofficial
Home Page: https://www.statlearning.com/
regularization-methods, These training sessions in machine learning, conducted by Yandex, are dedicated to classical machine learning. This offers an opportunity to reinforce theoretical knowledge through practice on training tasks.
User: tikhon-radkevich
Home Page: https://yandex.ru/yaintern/training/ml-training#polnoe-raspisanie
regularization-methods,System developed by team datamafia in WNUT 2020 Task 2: Identification of informative COVID-19 English Tweets
User: victor7246
regularization-methods,This repository contains a Python implementation of linear regression, logistic regression, and ridge regression algorithms. These algorithms are commonly used in machine learning and statistical modeling for various tasks such as predicting numerical values, classifying data into categories, and handling multicollinearity in regression models.
User: wangyuhsin
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