leaky-relu

yaricom/TimeSeriesLearning

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

MrDavidYu/TF_Convolutional_Autoencoder

Convolutional autoencoder for encoding/decoding RGB images in TensorFlow with high compression ratio

AFAgarap/vanishing-gradients

Avoiding the vanishing gradients problem by adding random noise and batch normalization

abhilash1910/GraphAttentionNetworks

This package is a Tensorflow2/Keras implementation for Graph Attention Network embeddings and also provides a Trainable layer for Multihead Graph Attention.

volkansonmez/Neural_Networks_From_Scratch

Deep Learning Projects

himasai97/GANs

Building Generative Adversarial Networks

Iheuzio/TickerPricePrediction

The code implements a neural network model, PricePredictor, trained on historical stock price data to predict future stock prices, visualizing the predictions alongside historical prices and calculating the average of the predicted prices.

mmaric27/BasicDNN

Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.

prabormukherjee/Layers_creation

Creating your own custom layers(Leaky ReLU) with Keras

RPGupta30/Activation-Functions

SameetAsadullah/Neural-Network-Implementation

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)

AVINASH-KURREY/DEEP-LEARNING

INTRODUCTION OF DEEP LEARNING

BharatGuturi/Alphabet-Soup-Charity-Deep-Learning

Using the features in the provided dataset, creating a binary classifier that can predict whether applicants will be successful if funded by Alphabet Soup.

tuhinaprasad28/Image-Classification-Using-Keras-and-Tensorflow--Feedforward-Neural-Networks

Image Classification, Python, Feedforward-Neural-Network, Tensorflow, Keras, CNN, ReLu

kuntala-c/Deep-Neural-Network-using-Cifar-10-dataset

Deep Learning concepts practice using Cifar-10 dataset

nafisa-samia/Implementing-Deep-Neural-Network-for-the-CIFAR-10-dataset

Deep Learning concepts practice using Cifar-10 dataset

neural-tangjie/NTJ-DL-Activation_Functions_in_Neural_Network

:octocat: This repository summarizes the basic concepts, types and usage scenarios of activation functions in deep learning.

omkarnitsureiitb/Satellite_to_Maps_GAN

Trained a generative Adverserial Network (GAN) which when given the satellite image of a place as input, outputs the Map image of that same location. It was trained using standard adverserial training.

srinadhu/AML_Assignments

Advance Machine Learning (CSL 712) Course Lab Assignments

vyomshm/Keras-predicting-random-file-transfer-durations

Jupyter notebooks to create random file transfer data on an ElasticSearch Cluster in order to train a neural network to predict the file transfer duration.

ZJEydt/CNeuron

CNeuron is a simple singular neural network neuron implementation in C, designed for easy integration into C projects.