Topic: hidden-layers Goto Github
Some thing interesting about hidden-layers
Some thing interesting about hidden-layers
hidden-layers,
User: aatifsohail191
hidden-layers,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
hidden-layers,Implementation of Artificial Neural Networks using NumPy
User: ahmedfgad
Home Page: https://pygad.readthedocs.io
hidden-layers,Implements Back propagation algorithm for multi-layer perceptron in incremental mode
User: ahmedshoaib
hidden-layers,The nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures
User: annbelbella
hidden-layers,Threat Detection System using Hybrid (Machine Learning + Lexical Analysis) learning Approach.
User: anubhavsaxena14
hidden-layers,CNN Deep Layer Filters Visualization using Tensorflow.
User: anujdutt9
hidden-layers,A neural network (NN) having two hidden layers is implemented, besides the input and output layers. The code gives choise to the user to use sigmoid, tanh orrelu as the activation function. Prediction accuracy is computed at the end.
User: ashwanikumarkashyap
hidden-layers,Feed Forward Neural Network to classify the FB post likes in classes of low likes or moderate likes or high likes, back propagtion is implemented with decay learning rate method
User: atul04
hidden-layers,The code of forward propagation , cost function , backpropagation and visualize the hidden layer.
User: chiapeilin
hidden-layers,simple neural network library in ANSI C
User: codeplea
Home Page: https://codeplea.com/genann
hidden-layers,Deep Neural Network Classifier for the Win/Linux/OSX platform based on the GTK# Framework
User: daelsepara
hidden-layers,A sklearn-driven script to learn the best parameters for MLP to classify a thyroid dataset
User: fredericoschardong
hidden-layers,An easy neural network for Java!
User: goessl
hidden-layers,A implementation of a Neural Network in vanilla python that trains on the MNIST handwritten digit classifiction problem.
User: harveybrezinaconniffe
hidden-layers,one layer and two layer neural networks
User: hknakst
hidden-layers,Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer
User: ishan7390
hidden-layers,Multi hidden layers neural network in Octave for classification as generalization from Stanford Class CS229 on Machine learning
User: jde65
hidden-layers,NU Bootcamp Module 21
User: jleigh101
hidden-layers,Deep-Learning neural network to analyze and classify the success of charitable donations.
User: karla-flores
hidden-layers,Genann library port to C#, simple neural network library in ANSI C
User: lanzaschneider
hidden-layers,Genann library port to C# (unsafe version), simple neural network library
User: lanzaschneider
hidden-layers, Illustrate how to show output of images between hidden layers.
User: mntalha
hidden-layers,An neural network to classify the handwritten digits 0-9 for the MNIST dataset. No NN/ML libraries used.
User: nathansamsel
hidden-layers,Python neural network built from scratch. Uses Machine Learning algorithms to correctly classify handwritten numbers into digits.
User: nikhildagarwal
hidden-layers,Neural backpropagation with examples and training (Java)
User: openworld42
hidden-layers,Javascript powered 'Multiple Choices Question' about Javascript fundamentals. Features 20 questions x 4 choices = 80 choices to pick from, a 5 minutes time limit, bonus and penalty points, on/off high score table featuring player names, points. High score table can be cleared at any moment. 100% Vanilla JS.
User: palowenstein
Home Page: https://palowenstein.github.io/kevin-flynn-js-quizz/
hidden-layers,Implementation of Neural Style Transfer algorithm with PyTorch library
User: parham1998
hidden-layers,"Deep Neural Network" from Scratch
User: pegah-ardehkhani
hidden-layers,"One Hidden Layer Neural Network" from Scratch
User: pegah-ardehkhani
hidden-layers,In this project, we build and train a model to predict if a customer will defer on a particular loan on an imbalanced dataset. We'll build a layered ANN for this and try to make our model better using Hyperparamater Optimization, before exploring Oversampling to make it more accurate.
User: pranavtumkur
hidden-layers,Implementing a 2-class Classification Neural Network with a Single Hidden Layer
User: prateeksawhney97
hidden-layers,Implementing a 2-class classification neural network with a single hidden layer. Using units with a non-linear activation function such as tanh. Computing the cross entropy loss. Implementing forward and backward propagation.
User: rajeshidumalla
hidden-layers,Prediction of Students' Academic Performance Dataset: Cart Trees, Random Forest, Cross Validation and Neuralnet
User: ramapitecusment
hidden-layers,Looking at the manifold hypothesis in deep learning. Creating a simple spiral dataset allows me to reveal how neural networks follow an optimal packing strategy during their training.
User: ranlot
hidden-layers,Create a neural network through TensorFlow and Keras to build a model which has the ability to assess an organisation's ability to be successful with funding from the Alphabet Soup charity
User: rjbarker
hidden-layers,A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
User: rtflynn
hidden-layers,This project is build up completely with numpy. It implements basic neural network concepts including backpropagation, hidden layers, activation function and gradient descent.
User: satyaki0924
hidden-layers,Visualisation of Hidden layers of a Sequential model
User: sbharadwajj
hidden-layers,Using keras specify-compile-fit- predict workflow on this binary classification problem to investigate if i'll get better predictions.
User: shuyib
hidden-layers,This is an ANN model template which uses a tanh activation function on an existing make_moons dataset. The number of hidden layers can be increased to improve prediction precision and accuracy.
User: siddhant-ray
hidden-layers,Deep Learning
User: singhgaurav2323
hidden-layers,Neural Networks scratch
User: soheilabadifard
hidden-layers,Snoop can be used to expand shortened Links such as those from bit.ly etc.to their original form without actually visting them. right from your terminal
User: vrikodar
hidden-layers,Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.
User: xaheli
hidden-layers,This code implements neural network from scratch without using any library
User: yashodhanvivek
hidden-layers,Deep Learning projects
User: zenetio
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