Topic: cross-entropy-loss Goto Github
Some thing interesting about cross-entropy-loss
Some thing interesting about cross-entropy-loss
cross-entropy-loss,Machine Learning: Regression and Classification. Andrew presents a course in introduction to machine learning, with practice in regression and classification for the first and second course, and the third course focuses on recommender systems and reinforcement learning.
User: abdoelabassi
Home Page: https://www.coursera.org/specializations/machine-learning-introduction
cross-entropy-loss,This repository contains two models having Two - layers ANN and L - layers ANN respectively to classify Cat photo and Non-Cat photo. This ANN works on the mathematical principles of Logistic Regression and Cross Entropy.
User: abhijit2505
cross-entropy-loss,Predict whether the cancer is benign or malignant using logistic regression model.
User: ad7amstein
cross-entropy-loss, Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
Organization: ai-med
Home Page: https://shayansiddiqui.github.io/nn-common-modules/build/html/
cross-entropy-loss,• Machine Learning •
User: alexkalergis
cross-entropy-loss,A PyTorch implementation of U-Net for aerial imagery semantic segmentation.
User: amirhosseinh77
cross-entropy-loss,Random experiments with scikit-learn.
User: ankush7890
cross-entropy-loss,We classified Stack Overflow Python questions from 2008-2016 with Natural Language Processing and Deep Learning. Using Regular Expressions, we removed HTML tags and punctuation. We also utilized spaCy to tokenize, lemmatize and remove stop words. Using Keras, we built a 4 layered artificial neural network with a 20% dropout rate using relu and softmax activation functions. We also utilized the adam optimizer and categorical cross-entropy loss function which classified 11 tags 88% successfully.
User: asaficontact
cross-entropy-loss, In the project, the aim is to generate new song lyrics based on the artist’s previously released song’s context and style. We have chosen a Kaggle dataset of over 57,000 songs, having over 650 artists. The dataset contains artist name, song name, a link of the song for reference & lyrics of that song. We tend to create an RNN character-level language model on the mentioned dataset. Using model evaluation techniques, the model is checked for its accuracy and is parameter optimized. The trained model will predict the next character based on the context of the previous sequence and will generate new lyrics based on an artist’s style.
User: ashwanikumarkashyap
cross-entropy-loss,This repository contains code for pretraining Wide Residual Network (WRN) using ImageNet
User: attaullah
cross-entropy-loss,This repository contains code for the PhD thesis: "A Study of Self-training Variants for Semi-supervised Image Classification" and publications.
User: attaullah
cross-entropy-loss,Neural Networks from scratch (Inspired by Michael Nielsen book: Neural Nets and Deep Learning)
User: beingbat
cross-entropy-loss,Neural network-based character recognition using MATLAB. The algorithm does not rely on external ML modules, and is rigorously defined from scratch. A report is included which explains the theory, algorithm performance comparisons, and hyperparameter optimization.
User: chrisshaffer
cross-entropy-loss,Maths behind machine learning and some implementations from scratch.
User: daodavid
cross-entropy-loss,MSc Thesis at FER-2021/22 led by izv. prof. dr. sc. Marko Čupić
User: dbrcina
cross-entropy-loss,Simple Implementation of Gradient Boosted Trees
User: dkohlsdorf
cross-entropy-loss,Decision Tree Implementation from Scratch
User: fakemonk1
Home Page: http://ashishgupta.me/
cross-entropy-loss,In this notebook, we want to create a machine learning model to accurately predict whether patients have a database of diabetes or not.
User: farkoo
cross-entropy-loss,A simple demo in which a Neural Network is trained to recognize hand-written digits
User: gavalle94
cross-entropy-loss,Code for the Paper : NBC-Softmax : Darkweb Author fingerprinting and migration tracking (https://arxiv.org/abs/2212.08184)
User: gayanku
cross-entropy-loss,Фреймворк глубоко обучения на Numpy, написанный с целью изучения того, как все работает под "капотом".
User: grafit24
cross-entropy-loss,In this X-ray classification assignment, we built a deep learning model to classify chest X-ray images into "nofinding" and "effusion" classes. We tackled challenges like data augmentation, imbalanced classes, and used weighted cross-entropy to improve model performance. The goal was to identify abnormalities with high accuracy.
User: gvhemanth
cross-entropy-loss,I implemented a CNN to train and test a handwritten digit recognition system using the MNIST dataset. I also read the paper “Backpropagation Applied to Handwritten Zip Code Recognition” by LeCun et al. 1989 for more details, but my architecture does not mirror everything mentioned in the paper. I also carried out a few experiments such as adding different dropout rates, using batch normalization, and using different optimizers in the baseline model. Finally, I discuss the impact of experiments on the learning curves and testing performance.
User: hardikasnani
cross-entropy-loss,Implementation of key concepts of neuralnetwork via numpy
User: hwalsuklee
cross-entropy-loss,full visualization of netflix and movielense datasets with 89% accuraccy item2vec
User: inzamamuldu
Home Page: https://github.com/inzamamulDU/movielens-and-netflix-dataset-prediction-
cross-entropy-loss,Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer
User: ishan7390
cross-entropy-loss,Practice using PyTorch include data preprocessing, linear algebra, optimization, neural networks, CNNs, and more to cover ML and DL basics
User: ismaelmousa
cross-entropy-loss,C codes for the Arificial Intelligence Course and algorithms.
User: krishnadey30
cross-entropy-loss,Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
Organization: lancopku
Home Page: https://arxiv.org/abs/2110.06537
cross-entropy-loss,Implemented and trained Siamese network for image classification using contrastive loss, triplet loss and regularized cross-entropy loss
User: mansi-k
cross-entropy-loss,A classifier to differentiate between Cat and Non-Cat Images
User: mb11797
cross-entropy-loss,Breast Cancer Classification with Logistic Regression
User: parismollo
cross-entropy-loss,Evaluated the word vectors learned from both nce and cross entropy loss functions using word analogy tests
User: pkpraveen895
cross-entropy-loss,KL severity grading using SE-ResNet and SE-DenseNet architectures trained with Cross Entropy loss and Focal Loss. The hyperparameters of focal loss have been fine-tuned as well. Further, Grad-CAM has been implemented for visualization purposes.
User: rae-t627
cross-entropy-loss,The most basic LSTM tagger model in pytorch; explain relationship between nll loss, cross entropy loss and softmax function.
User: rantsandruse
cross-entropy-loss,Word2Vec implementation using tensorflow
User: rmodi6
cross-entropy-loss,Deep Neural Networks like Single Layer Perceptron and Multi Layer Perceptron implementation using Tensorflow library on Datasets like MNIST and Naval Mine for categorical Classification. Saving and Restoring Tensorflow "Variables" weights for testing.
User: rnk20
cross-entropy-loss,This repo contains the assignments and projects for the AI course offered at IIIT-SriCity
User: rsk97
cross-entropy-loss,Neural Network implemented with different Activation Functions i.e, sigmoid, relu, leaky-relu, softmax and different Optimizers i.e, Gradient Descent, AdaGrad, RMSProp, Adam. You can choose different loss functions as well i.e, cross-entropy loss, hinge-loss, mean squared error (MSE)
User: sameetasadullah
cross-entropy-loss,Digital Image Processing Course | Home Works Design| Fall 2021 | Dr. MohammadReza Mohammadi
User: saminheydarian
cross-entropy-loss,The MNIST dataset was used to train a neural network having a single linear layer with SoftMax employed in the criterion function (Cross Entropy Loss) to classify handwritten digits in classes 0 to 9. The model yielded a 92% accuracy on the MNIST test dataset in 10 training epochs.
User: sharmeen-k
cross-entropy-loss,Multiclass Classification using Softmax from scratch without any famous library like Tensorflow, Pytorch, etc.
User: singh-jagjot
cross-entropy-loss,Image Classification using Neural Networks
User: swethalahari
cross-entropy-loss,Binary and Categorical Focal loss implementation in Keras.
User: umbertogriffo
cross-entropy-loss,Comparison of common loss functions in PyTorch using MNIST dataset
User: unvercan
cross-entropy-loss,A Feed Forward Neural Network which a ReLU activation, Cross Entropy Loss & Adam Optimizer
User: usmanniazi
cross-entropy-loss,Web application for clasifying handwritten digits.
User: vlasakjiri
Home Page: http://handwrittennumberclassifier.azurewebsites.net/
cross-entropy-loss,Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"
User: yisenwang
Home Page: https://arxiv.org/abs/1908.06112
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