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.
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
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
Making a Deep Learning Framework with C++
FloydHub porting of deeplearning.ai course assignments
Neural Networks: Zero to Hero. I completed the tutorial series by Andrej Karpathy
Comapring different methods of weight initialization and optimizers using PyTorch
Interactive demos of neural network weight initialization.
This repository showcases a structured and progressive approach to training a Convolutional Neural Network (CNN) for binary image classification (cats vs dogs).
Mathematical and empirical investigations of neural network optimization, activation functions, and weight initialization
This repo will describe the preparation process of deep learning weights before the training to capture essential information about data fed
Use ML-FLOW and TensorFlow2.0(Keras) to record all the experiments on the Fashion MNIST dataset.
Neural Network
Everything about Artificial Neural Network from Basic to Adavnced
Deep Learning with TensorFlow Keras and PyTorch
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