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All the code files related to the deep learning course from PadhAI
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks
A module for making weights initialization easier in pytorch.
A curated list of awesome deep learning techniques for deep neural networks training, testing, optimization, regularization etc.
PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
Neural_Networks_From_Scratch
How weight initialization affects forward and backward passes of a deep neural network
FloydHub porting of deeplearning.ai course assignments
Neural Networks: Zero to Hero. I completed the tutorial series by Andrej Karpathy
RNN-LSTM: From Applications to Modeling Techniques and Beyond - Systematic Review
Deep Learning with TensorFlow Keras and PyTorch
This repository explores the impact of various weight initialization methods on a neural network's performance, comparing zero, random, and He initialization. It includes visualizations of cost function and decision boundaries.
Everything about Artificial Neural Network from Basic to Adavnced
Neural Network
Comapring different methods of weight initialization and optimizers using PyTorch
Why don't we initialize the weights of a neural network to zero?
MachineLearningCurves is a collection of abstract papers, insights, and research notes focusing on various topics in machine learning.
Playground for trials, attempts and small projects.
This repo will describe the preparation process of deep learning weights before the training to capture essential information about data fed
Data driven initialization for neural network models
Variance normalising pre-training of neural networks.
Use ML-FLOW and TensorFlow2.0(Keras) to record all the experiments on the Fashion MNIST dataset.
This code implements neural network from scratch without using any library