Topic: l2-regularization Goto Github
Some thing interesting about l2-regularization
Some thing interesting about l2-regularization
l2-regularization,1. Understand how neural networks work 2. Implement a simple neural network 3. Understand the role of different parameters of a neural network, such as learning rate
User: adityachechani
l2-regularization,Repository for Assignment 1 for CS 725
User: akshaykhadse
l2-regularization,Analysis of the robustness of non-negative matrix factorization (NMF) techniques: L2-norm, L1-norm, and L2,1-norm
User: alejandrods
l2-regularization,Implementation of optimization and regularization algorithms in deep neural networks from scratch
User: aliyzd95
l2-regularization,I executed this assignment for a US-based housing company named Surprise Housing, wherein a regression model with regularisation was used to predict the actual value of the prospective properties and decide whether to invest in them or not
User: ayan-chattaraj
l2-regularization,The dataset that I am performing this regression analysis on, comes from Kaggle, titled crimes In India. This dataset holds complete information about various aspects of crimes that have taken place in India in a 17 year span, from 2001 to 2018.
User: benitadiop
l2-regularization,Simple Demo to show how L2 Regularization avoids overfitting in Deep Learning/Neural Networks
User: bhattbhavesh91
l2-regularization,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.
User: bohaterewicz
l2-regularization,Identifying text in images in different fonts using deep neural network techniques.
User: cnavneet
l2-regularization,House Price Analysis and Sales Price Prediction
User: darshil2848
l2-regularization,Regularized Logistic Regression
Organization: dedupeio
l2-regularization,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
User: dunittmonagas
l2-regularization,Machine Learning Course [ECE 501] - Spring 2023 - University of Tehran - Dr. A. Dehaqani, Dr. Tavassolipour
User: fardinabbasi
l2-regularization,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.
User: federicoarenasl
l2-regularization,Multivariate Regression and Classification Using a Feed-Forward Neural Network and Gradient Descent Optimization.
User: gabrielegilardi
l2-regularization,Multivariate Linear and Logistic Regression Using Gradient Descent Optimization.
User: gabrielegilardi
l2-regularization,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.
User: ghazaleze
l2-regularization,A study of the problem of overfitting in deep neural networks, how it can be detected, and prevented using the EMNIST dataset. This was done by performing experiments with depth and width, dropout, L1 & L2 regularization, and Maxout networks.
User: hwixley
l2-regularization,MITx - MicroMasters Program on Statistics and Data Science - Data Analysis: Statistical Modeling and Computation in Applications - Second Project
User: jajokine
l2-regularization,Modifiable neural network
User: jamesneve
l2-regularization,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.
User: kanishknavale
l2-regularization,Chapman University CS-510 Computing For Scientists Final Project
User: kashishpandey
l2-regularization,An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.
User: kinoute
l2-regularization,My java implementation of scalable on-line stochastic gradient descent for regularized logistic regression
User: lingxuez
l2-regularization,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.
User: mansipatel2508
Home Page: https://colab.research.google.com/drive/1cymmyp2Bz-nYPKPnJNxtZdlYd7kdKhjd
l2-regularization,Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.
User: mmaric27
l2-regularization,Water and lipid signal removal in MRSI by L2 regularization (submitted by Liangjie Lin)
User: mrshub
l2-regularization,This repository is about machine learning algorithms
User: nishanthbhat07
l2-regularization,linear regression with different types and datasets. Understanding of linear regression with Boston dataset using numpy.
User: praveen2812git
l2-regularization,Implementation of linear regression with L2 regularization (ridge regression) using numpy.
User: pwc2
l2-regularization,Creating Neural Net from scratch using python , Numpy.
User: rahil-07
l2-regularization,Comparision of Linear Regression, Ridge Regression, Lasso Regression
User: reshma78611
l2-regularization,Deep Learning Course | Home Works | Spring 2021 | Dr. MohammadReza Mohammadi
User: saminheydarian
l2-regularization,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
User: sandipanpaul21
l2-regularization,PyTorch implementation of important functions for WAIL and GMMIL
User: sapanachaudhary
l2-regularization,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.
User: shouryasimha
l2-regularization,The primary objective of this project is to design and train a deep neural network that can generalize well to new, unseen data, effectively distinguishing between rocks and metal cylinders based on the sonar chirp returns.
User: siddharthiyervarma
l2-regularization,Image Classification with CNN using Tensorflow backend Keras on Fashion MNIST dataset
User: sinturkgozde
l2-regularization,Short description for quick search
User: ssq
l2-regularization,A framework for implementing convolutional neural networks and fully connected neural network.
User: swikargautam
l2-regularization,Fully connected neural network with Adam optimizer, L2 regularization, Batch normalization, and Dropout using only numpy
User: swikargautam
l2-regularization,A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.
User: tayebiarasteh
l2-regularization,Фреймворк для построения нейронных сетей, комитетов, создания агентов с параллельными вычислениями.
User: the-lans
l2-regularization,Multiclass Logistic, Classification Pipeline, Cross Validation, Gradient Descent, Regularization
User: tuhinaprasad28
l2-regularization,Wrapper on top of liblinear-tools
User: unixjunkie
l2-regularization,Utilizing Logistic Regression to determine the likelihood of heart disease presence in an individual.
User: yarrap
l2-regularization,Mathematical machine learning algorithm implementations
User: zhangyongheng78
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