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Topic: "he-initializer"

Niranjankumar-c/DeepLearning-PadhAI

All the code files related to the deep learning course from PadhAI

Language: Jupyter Notebook - Size: 3.61 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 90 - Forks: 121

hwalsuklee/tensorflow-mnist-MLP-batch_normalization-weight_initializers

MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.

Language: Python - Size: 1.62 MB - Last synced at: 28 days ago - Pushed at: over 8 years ago - Stars: 55 - Forks: 17

YeongHyeon/Compare_Activation_Function

Compare vanishing gradient problem case by case.

Language: Python - Size: 219 KB - Last synced at: 22 days ago - Pushed at: about 6 years ago - Stars: 9 - Forks: 0

AdamYuan/SimpleNN

a simple neural network

Language: C++ - Size: 25.9 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 8 - Forks: 1

ElefHead/digit_recognition

Fully connected neural network for digit classification using MNIST data

Language: Python - Size: 11 MB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 4 - Forks: 2

mohadeseh-ghafoori/Coursera-Deep-Learning-Specialization

Language: Jupyter Notebook - Size: 4.83 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

mohadeseh-ghafoori/Initialization-Methods

Language: Jupyter Notebook - Size: 174 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

mohadeseh-ghafoori/Semantic-Image-Segmentation-with-U-Net

Language: Jupyter Notebook - Size: 520 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

GiacomoLeoneMaria/How-to-Increment-the-Accuracy-of-CNN-step-by-step

The aim of this project is to implement an image classifier based on convolu- tional neural networks. Starting by implementing a simple shallow network and then refining it until a pre-trained ResNet18 is implemented, showing at each step how the accuracy of the model improves. The provided dataset (from [Lazebnik et al., 2006]) contains 15 categories.

Language: Jupyter Notebook - Size: 980 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

byelipk/deeper-mnist

Using advanced deep learning techniques on the MNIST dataset. Over 98% validation set accuracy.

Language: Python - Size: 10.8 MB - Last synced at: almost 2 years ago - Pushed at: about 8 years ago - Stars: 0 - Forks: 0

Related Topics
adam-optimizer 5 numpy 3 tensorflow 3 mnist 3 batch-normalization 3 rmsprop 2 mnist-handwriting-recognition 2 xavier-initializer 2 lstm-neural-networks 2 semantic-segmentation 2 cnn 2 relu 1 sigmoid 1 van 1 problem-solving 1 gradient 1 deep-neural-networks 1 elu-activation 1 softmax-regression 1 sfml 1 bidirectional-rnn 1 neural-network 1 fine-tuning 1 xavier 1 weight-initializers 1 mnist-classification 1 he 1 yolo 1 u-net 1 triplet-loss 1 transfer-learning 1 rnn-tensorflow 1 regularization-dropout 1 one-hot-encoding 1 neural-style-transfer 1 neural-machine-translation 1 l2-regularization 1 iou 1 gram-matrix 1 data-augmentation 1 image-augmentation 1 pytorch 1 resnet-18 1 shallow-network 1 activation-functions 1 cnn-classification 1 python 1 pytorch-cnn 1 pytorch-tutorials 1 weight-initialization 1 amsgrad 1 classification 1 mnist-dataset 1 momentum 1 neural-networks 1 python3 1 deep-learning 1 initialization 1 matplotlib 1 random-initialization 1 zero-initialisation 1 concatenate 1 conv2d 1 dropout-layers 1 maxpool2d 1 maxpooling-layer 1 relu-activation 1 transpose-convolution 1 unet-model 1