All the code files related to the deep learning course from PadhAI
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Updated
Apr 13, 2020 - Jupyter Notebook
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.
Neural_Networks_From_Scratch
PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
A curated list of awesome deep learning techniques for deep neural networks training, testing, optimization, regularization etc.
Excel file, Presentation Slides, and Python code used in the published SLR paper: RNN-LSTM: From Applications to Modeling Techniques and Beyond - Systematic Review
How weight initialization affects forward and backward passes of a deep neural network
Making a Deep Learning Framework with C++
Neural Networks: Zero to Hero. I completed the tutorial series by Andrej Karpathy
FloydHub porting of deeplearning.ai course assignments
Deep Learning with TensorFlow Keras and PyTorch
This repo will describe the preparation process of deep learning weights before the training to capture essential information about data fed
Why don't we initialize the weights of a neural network to zero?
This repository showcases a structured and progressive approach to training a Convolutional Neural Network (CNN) for binary image classification (cats vs dogs).
Comapring different methods of weight initialization and optimizers using PyTorch
MachineLearningCurves is a collection of abstract papers, insights, and research notes focusing on various topics in machine learning.
Everything about Artificial Neural Network from Basic to Adavnced
Variance normalising pre-training of neural networks.
Data driven initialization for neural network models
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