l2-regularization

There are 0 repository under l2-regularization topic.

indranil143 / Mental-Health-Sentiment-Analysis-using-Deep-Learning
A deep learning project using fine-tuned RoBERTa to classify mental health sentiments from text, aiming to provide early insights and support. ⚕️❤️
deep-learning eda emotion-detection logistic-regression machine-learning mental-health mental-health-awareness mentalsupport ngrams nlp python pytorch roberta sentiment-analysis transformermodel nltk spacy l2-regularization sentiment-classification
Language:Jupyter Notebook 28
sandipanpaul21 / Logistic-regression-in-python
Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value
logistic-regression regularization l1-regularization l2-regularization lasso-regression ridge-regression elastic-net-regression multiclass-logistic-regression weight-of-evidence information-value logistic-regression-assumptions
Language:Jupyter Notebook 18
the-lans / NeuroRepository
Фреймворк для построения нейронных сетей, комитетов, создания агентов с параллельными вычислениями.
neural-networks neuronal-network neuralnetworks neural-nets framework qtcreator std qt5 qt csv-export backpropagation backpropagation-algorithm backprop backpropagation-neural-network trade mse crossentropy l2-regularization dropout
Language:C++ 18
SSQ / Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization
Short description for quick search
initialization gradient-check l2-regularization dropout mini-batch-gradient-descent exponentially-weighted-averages bias-correction momentum rmsprop adam-optimizer learning-rate-decay batch-normalization softmax-regression tensorflow
Language:Python 17
alejandrods / Analysis-of-the-robustness-of-NMF-algorithms
Analysis of the robustness of non-negative matrix factorization (NMF) techniques: L2-norm, L1-norm, and L2,1-norm
nmf non-negative-matrix-factorization matrix-factorization robustness python l2-norm l2-regularization l1-norm l21-norm factorization machine-learning deep-learning data-science noise image-classification nlp
Language:Jupyter Notebook 11
dedupeio / rlr
Regularized Logistic Regression
logistic-regression python l2-regularization
Language:Python 11
mansipatel2508 / Network-Intrusion-Detection-with-Feature-Extraction-ML
The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.
network-intrusion-detection feature-extraction feature-selection feature-importance binary-classification multiclass-classification confusion-matrix roc-curve pearson-correlation-coefficient rfe l1-regularization l2-regularization fclassif select-percentile extrat-tree-classifier rfc
Language:Jupyter Notebook 11
jamesneve / go-neural-network
Modifiable neural network
golang neural-network backpropagation stochastic-gradient-descent l2-regularization
Language:Go 7
UnixJunkie / linwrap
Wrapper on top of liblinear-tools
liblinear linear-svm classification ocaml-program logistic-regression l2-regularization lrl2 linear-svr machine-learning
Language:OCaml 7
mrshub / Wat_Lip_Removal_L2
Water and lipid signal removal in MRSI by L2 regularization (submitted by Liangjie Lin)
mrshub magnetic-resonance-spectroscopy mrs l2-regularization
Language:MATLAB 5
sjsreehari / Heart-Risk-Detector-NeuralNetwork
Implemented a neural network from scratch in Python with just NumPy, no frameworks involved.
backpropagation data-preprocessing feedforward-neural-network l2-regularization machine-learning ml-project neural-network numpy python
Language:Python 5
ArshTiwari2004 / Sahyog
Centralized Disaster Response and Inventory Management System that leverages AI and Google Cloud Technologies to predict disasters, optimize resource management, and provide real-time coordination.
apache-kafka apache-spark cnn-classification gan-models hyperledger-fabric lstm-model yolov8-detection tensorflow adam-optimizer docker efficientnetb4 gcp-storage gcs gemini-api keras-classification-models l2-regularization numpy opencv twilio vertex-ai
Language:JavaScript 4
DunittMonagas / Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization
Curso Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization. Segundo curso del programa especializado Deep Learning. Este repositorio contiene todos los ejercicios resueltos. https://www.coursera.org/learn/neural-networks-deep-learning
gradient-check gradient-descent stochastic-gradient-descent momentum rmsprop adam-optimizer mini-batch-gradient-descent dropout l2-regularization tensorflow hyperparameter-tuning batch-normalization
Language:Jupyter Notebook 4
kinoute / Elyane
An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.
neural-network deep-learning oop python adam-optimizer rmsprop momentum l2-regularization dropout softmax
Language:Python 4
mohadeseh-ghafoori / Coursera-Deep-Learning-Specialization
adam-optimizer he-initializer lstm-neural-networks rmsprop rnn-tensorflow u-net yolo l2-regularization regularization-dropout bidirectional-rnn one-hot-encoding batch-normalization iou semantic-segmentation data-augmentation transfer-learning gram-matrix neural-machine-translation neural-style-transfer triplet-loss
Language:Jupyter Notebook 3
SapanaChaudhary / PyTorch-IL-functions
PyTorch implementation of important functions for WAIL and GMMIL
imitation-learning pytorch gaussian-kernel entropy-regularizer l2-regularization deep-imitation-learning inverse-reinforcement-learning
Language:Python 3
SawyerAlston / MNIST-NN-Pure-Math
A "from-scratch" 2-layer neural network for MNIST classification built in pure NumPy, featuring mini-batch gradient descent, momentum, L2 regularization, and evaluation tools — no ML libraries used.
confusion-matrix deep-learning l2-regularization machine-learning mini-batch-gradient-descent mlp-classifier mnist neural-network numpy
Language:Python 3
bhattbhavesh91 / regularization-neural-networks
Simple Demo to show how L2 Regularization avoids overfitting in Deep Learning/Neural Networks
regularization l2-regularization deep-learning neural-networks keras keras-neural-networks keras-tensorflow overfitting
Language:Jupyter Notebook 2
KanishkNavale / Text-Mining-with-TF-IDF-and-Cosine-Similarity
A simple python repository for developing perceptron based text mining involving dataset linguistics preprocessing for text classification and extracting similar text for a given query.
text-classification text-mining nltk tf-idf cosine-similarity-scores perceptron l2-regularization linguistics tokenization lemmatization information-retreival machine-learning optimization torch-sparse-matrix
Language:Jupyter Notebook 2
TwentyOneError / simple_neural_works
The module allows working with simple neural networks (Currently, the simplest model of a multilayer perceptron neural network with the backpropagation method and the Leaky ReLu activation function is used).
l1-regularization l2-regularization leakyrelu library machine-learning neural-networks perceptron-neural-networks
Language:Python 2
abisliouk / IE675b-machine-learning
This is a repository with the assignments of IE675b Machine Learning course at University of Mannheim.
dirichlet-distribution naive-bayes-classifier cross-validation map-estimation multinomial-naive-bayes gradient-descent l2-regularization logistic-regression mle-estimation normalization stochastic-gradient-descent gaussian-prior gmm-clustering lvm svd
Language:Jupyter Notebook 1
aliyzd95 / Optimization-and-Regularization-from-scratch
Implementation of optimization and regularization algorithms in deep neural networks from scratch
deep-learning deep-neural-networks optimization optimization-algorithms regularization regularization-methods adagrad adam gradient-descent rmsprop l1-regularization l2-regularization cifar cifar-10 cifar10
Language:Python 1
bohaterewicz / Sales_forecasting_model
The aim was to create and implement a predictive model that can forecast the number of items sold for a period of 8 weeks ahead.
count-based forecasting-models l2-regularization poisson-distribution prediction-model regression-models sales
Language:Jupyter Notebook 1
fardinabbasi / Logistic_Regression
Implementing logistic regression with L2 regularization from scratch to classify circular datasets by mapping the feature space into higher dimensions.
feature-mapping l2-regularization logistic-regression
Language:Jupyter Notebook 1
federicoarenasl / Regularization-techniques-on-NNs
During this study we will explore the different regularisation methods that can be used to address the problem of overfitting in a given Neural Network architecture, using the balanced EMNIST dataset.
neural-networks l2-regularization l1-regularization dropout machine-learning deep-learning data-science
Language:Jupyter Notebook 1
gabrielegilardi / FeedForwardNN
Multivariate Regression and Classification Using a Feed-Forward Neural Network and Gradient Descent Optimization.
python classification regression multivariate feedforward-neural-network gradient-descent-optimizer backpropagation-algorithm l2-regularization
Language:Python 1
GhazaleZe / Investigate_Classifiers
The point is to investigate three types of classifiers (linear classifier with feature selection, linear classifier without feature selection, and a non-linear classifier) in a setting where precision and interpretability may matter.
feature-selection l2-regularization large-scale lasso-regression machine-learning random-forest-classifier support-vector-machine svm-classifier
Language:Jupyter Notebook 1
BasicDNN
mmaric27 / BasicDNN
Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.
deep-neural-network python numpy l-layer-neural-network sigmoid relu leaky-relu tanh softmax gradient-descent mini-batch-gradient-descent adam-optimizer momentum-optimization-algorithm l2-regularization drop-out-layer weights-initialization xavier-initializer he-initializer fully-connected-network neural-network
Language:Python 1
MoinDalvs / Different_types_Linear_Regressions
data-science linear l1-regularization l2-regularization lasso-regression linear-regression polynomial-regression ridge-regression
Language:Jupyter Notebook 1
pwc2 / ridge-regression
Implementation of linear regression with L2 regularization (ridge regression) using numpy.
ridge-regression machine-learning l2-regularization batch-gradient-descent
Language:Python 1
saminheydarian / DeepLearning_Course_2021
Deep Learning Course | Home Works | Spring 2021 | Dr. MohammadReza Mohammadi
self-supervised-learning fine-tuning adam-optimizer image-captioning backpropagation time-series facial-expression-recognition sgd-optimizer deep-q-network spaceinvaders-v0 data-augmentation l2-regularization cnn rnn naive-bayes-classifier logistic-regression seq2seq-model batch-normalization triplet-loss pretext-task
Language:Jupyter Notebook 1
shouryasimha / Ships-In-Satellite-images
Satellite imagery provides unique insights into various markets, including agriculture, defense and intelligence, energy, and finance. New commercial imagery providers, such as Planet, are using constellations of small satellites to capture images of the entire Earth every day. This flood of new imagery is outgrowing the ability for organizations to manually look at each image that gets captured, and there is a need for machine learning and computer vision algorithms to help automate the analysis process. The aim is to help address the difficult task of detecting the location of large ships in satellite images. Automating this process can be applied to many issues including monitoring port activity levels and supply chain analysis.
satellite-images imagery ships keras-neural-networks dropout l2-regularization resnet-50 vgg16 training visualization
Language:Jupyter Notebook 1
sinturkgozde / Keras-CNN-Fashion-MNIST
Image Classification with CNN using Tensorflow backend Keras on Fashion MNIST dataset
keras-tensorflow image-classification cnn l2-regularization matplotlib fashion-mnist
Language:Jupyter Notebook 1
SwikarGautam / ConvoNet
A framework for implementing convolutional neural networks and fully connected neural network.
convolutional-neural-networks fully-connected-network numpy batch-normalization adam-optimizer dropout l2-regularization
Language:Python 1
SwikarGautam / DeepDenseNetwork
Fully connected neural network with Adam optimizer, L2 regularization, Batch normalization, and Dropout using only numpy
l2-regularization adam-optimizer dropout batch-normalization numpy vanilla-neural-network
Language:Python 1
zhangyongheng78 / Mathematical-Machine-Learning-Algorithm-Implementations
Mathematical machine learning algorithm implementations
kernel-prediction l1-regularization l2-regularization lda svm generative-model neural-networks machine-learning
Language:Python 1

l2-regularization

indranil143 / Mental-Health-Sentiment-Analysis-using-Deep-Learning

sandipanpaul21 / Logistic-regression-in-python

the-lans / NeuroRepository

SSQ / Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

alejandrods / Analysis-of-the-robustness-of-NMF-algorithms

dedupeio / rlr

mansipatel2508 / Network-Intrusion-Detection-with-Feature-Extraction-ML

jamesneve / go-neural-network

UnixJunkie / linwrap

mrshub / Wat_Lip_Removal_L2

sjsreehari / Heart-Risk-Detector-NeuralNetwork

ArshTiwari2004 / Sahyog

DunittMonagas / Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

kinoute / Elyane

mohadeseh-ghafoori / Coursera-Deep-Learning-Specialization

SapanaChaudhary / PyTorch-IL-functions

SawyerAlston / MNIST-NN-Pure-Math

bhattbhavesh91 / regularization-neural-networks

KanishkNavale / Text-Mining-with-TF-IDF-and-Cosine-Similarity

TwentyOneError / simple_neural_works

abisliouk / IE675b-machine-learning

aliyzd95 / Optimization-and-Regularization-from-scratch

bohaterewicz / Sales_forecasting_model

fardinabbasi / Logistic_Regression

federicoarenasl / Regularization-techniques-on-NNs

gabrielegilardi / FeedForwardNN

GhazaleZe / Investigate_Classifiers

mmaric27 / BasicDNN

MoinDalvs / Different_types_Linear_Regressions

pwc2 / ridge-regression

saminheydarian / DeepLearning_Course_2021

shouryasimha / Ships-In-Satellite-images

sinturkgozde / Keras-CNN-Fashion-MNIST

SwikarGautam / ConvoNet

SwikarGautam / DeepDenseNetwork

zhangyongheng78 / Mathematical-Machine-Learning-Algorithm-Implementations