Topic: tuning-parameters Goto Github
Some thing interesting about tuning-parameters
Some thing interesting about tuning-parameters
tuning-parameters,Creating a good Convolutional Neural Network to classify our data. I used Model Checking to save the best model and VGG16 and ResNet50 to leverage pre-trained models. I ultimately used pre-trained models to fine tune a model.
User: amirhhasani
tuning-parameters,Hyper-parameter + encoding + architecture grid/random search for keras
User: amirziai
tuning-parameters,we fit various splines to model the COVID-19 daily positive case numbers in Florida from 3/3/20 – 3/7/21.
User: arek-kesizabnousi
tuning-parameters,Parallel Hyperparameter Tuning in Python
Organization: arm-software
tuning-parameters,The project includes building seven different machine learning classifiers (including Linear Regression, Decision Tree, Bagging, Random Forest, Gradient Boost, AdaBoost, and XGBoost) using Original, OverSampled, and Undersampled data of ReneWind case study, tuning hyperparameters of the models, performance comparisons, and pipeline development for productionizing the final model.
User: ayda-darvishan
tuning-parameters,A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.
User: cerlymarco
tuning-parameters,Swarming behaviour is based on aggregation of simple drones exhibiting basic instinctive reactions to stimuli. However, to achieve overall balanced/interesting behaviour the relative importance of these instincts, as well their internal parameters, must be tuned. In this project, you will learn how to apply Genetic Programming as means of such tuning, and attempt to achieve a series of non-trivial swarm-level behaviours.
User: cheejyg
tuning-parameters,Fractional order proportional derivative controller tuner
User: cnpcshangbo
tuning-parameters,In this repository, a regression analysis is conducted using different machine learning and deep learning models. The study is led in order to choose the most suitable model by looking at different characteristics (models tuning, features scaling, etc).
User: davidcico
tuning-parameters,A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.
User: davidenardone
tuning-parameters,Implementation of Deep-learning techniques in pytorch
User: divya-bhargavi
tuning-parameters,Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Organization: google
Home Page: https://oss-vizier.readthedocs.io
tuning-parameters,The distributed statistical machine translation infrastructure consisting of load balancing, text pre/post-processing and translation services. Written in C++ 11 and utilises multicore CPUs by employing multi-threading, allows for secure SSL/TLS communications.
User: ivan-zapreev
tuning-parameters,Easy Hyper Parameter Optimization with mlr and mlrMBO.
User: jakob-r
tuning-parameters,A Julia machine learning framework
Organization: juliaai
Home Page: https://juliaai.github.io/MLJ.jl/
tuning-parameters,Aplicação de conceitos da disciplina de Controle de Processos.
User: juliosdutra
tuning-parameters,How to Change Split Threshold for svchost.exe in Windows 10/11
User: kazheku
tuning-parameters,Loan Application Automation
User: kiptochmike
tuning-parameters,Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
User: liyanghart
tuning-parameters,a library to tune xgboost models
User: mainro
tuning-parameters,Implementation of a genetic algorithm to determine the parameters of the PID, PI-D, I-PD and PIDA controllers in order to compensate various benchmark processes, which are representative of many industrial applications. In particular, by considering separately a set-point and a load disturbance rejection unit step response the IAE is minimized by constraining the maximum sensitivity.
User: marco-milanesi
tuning-parameters,Monte Carlo Penalty Selection for graphical lasso
User: markkukuismin
tuning-parameters,Package for machine learning of astronomical objects such as light curves
User: mavrix93
tuning-parameters,Enhanced CNN model for malaria cell classification, featuring Class Activation Mapping (CAM) as a non-agnstic technique for anomaly localization and LIME (Local Interpretable-agnostic Explanation) for interpretability, ensuring high accuracy and transparent AI diagnostics.
User: mdhabibi
Home Page: https://www.kaggle.com/iarunava/cell-images-for-detecting-malaria
tuning-parameters,Classification-Diabetic-Machine Learning-Algorithm-Decision Tree-Improve by-Principle Component Analysis
User: michstg
tuning-parameters,Forecast price of basic commodities East Kalimantan using LSTM Algorithm and Exponential Smoothing
User: michstg
tuning-parameters,Open source cross-platform compiler for compute-intensive loops used in AI algorithms, from Microsoft Research
Organization: microsoft
Home Page: https://microsoft.github.io/Accera
tuning-parameters,A Predictive Model for Marketing Campaigns
User: miraytopal
tuning-parameters,Tuning Monte Carlo generators with machine learning.
Organization: n3pdf
Home Page: https://mcnntunes.readthedocs.io/
tuning-parameters,"oxayavongsa/projects" is a public GitHub repository serving as a diverse AI/ML Project Portfolio. Using Python coding and Juptyer notebook for multiple methodologies to model statistical algorithms.
User: oxayavongsa
Home Page: https://github.com/oxayavongsa/projects.git
tuning-parameters,Support Vector machine In detail: /implementation in Python&R/and tuning SVM parameters
User: prosperityai
tuning-parameters,🔥 A curated list of awesome links related to MySQL / MariaDB / Percona performance tuning
Organization: releem
tuning-parameters,Machine Learning Hyper-parameter Tuning processes
User: rgmantovani
tuning-parameters,Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data
User: romainkp
tuning-parameters,:trophy: Machine Learning Estimators
User: romellfudi
Home Page: https://romellfudi.github.io/MachineLearing/
tuning-parameters,Optimizing-Hyperparameters-Using-Grid-Search-Deep-Learning
User: saadhaxxan
tuning-parameters,MATLAB code for tuning a PID controller using Genetic Algorithm (GA)
User: sudhakarkuma
tuning-parameters,Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause
User: sushantdhumak
tuning-parameters,Deep Learning Nanodegree Project : To generate Simpsons TV scripts using part of the Simpsons data-set of scripts from 27 seasons.
User: sushantdhumak
tuning-parameters,A multi-thread code for tuning and running several clustering algorithms.
User: thainamariani
tuning-parameters,
User: thisislohith6
tuning-parameters,Autotuner for Spark applications
User: umayrh
tuning-parameters,XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!
User: vinbhaskara
tuning-parameters,Time Series Cross-Validation -- an extension for scikit-learn
User: wenjiez
Home Page: https://tscv.readthedocs.io
tuning-parameters,PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition
User: wgcban
Home Page: https://www.wgcban.com/research#h.wgch37qlgaku
tuning-parameters,R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process
User: ymattu
tuning-parameters,ECG Arrhythmia Detection with ResNet and Transfer Learning
User: ywan3223
tuning-parameters,A Magisk module for maximizing the digital audio fidelity by reducing jitters on audio outputs (USB DACs, Bluetooth a2dp, DLNA, etc.)
User: yzyhk904
tuning-parameters,⚛️ Deep Learning Specialization by deeplearning.ai
User: zhenye-na
Home Page: https://www.coursera.org/specializations/deep-learning
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