Master's project: Using Machine Learning for Potential Energy Landscapes
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Updated
May 14, 2018
Master's project: Using Machine Learning for Potential Energy Landscapes
Essential deep learning algorithms, concepts, examples and visualizations with TensorFlow. Popular and custom neural network architectures. Applications of neural networks.
Tensorflow, Template, Classic NN Architecture
Neural Network Prototyping library with reactive interface and export code features
Unofficial code with the paper "On the Role of Text Preprocessing in Neural Network Architectures" for IMDb dataset.
This repository is the implementation of several famous convolution neural network architecture with Keras. (Resnet v1, Resnet v2, Inception v1/GoogLeNet, Inception v2, Inception v3))
Deep Learning Algorithms implemented from scratch using Numpy
📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
Neural Network Architcture | ISI Kolkata
[arXiv'18] Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks
A toolkit for training CNN-1DRNN-CTC model to perform line-level Handwritten Text Recognition
Traffic Sign Classifier (project 3 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
Major Neural Network Architectures - recurrent neural networks, convolutional neural networks, long-short-term-memory, autoencoders, recommender systems, artificial general intelligence
Contains the architecture of neural network in python (without using any framework)
AAAI 2021. Neural Sequence-to-grid Module for Learning Symbolic Rules
Programming Assignments completed under first Course of Deep Learning Specialisation(Coursera)
An Open Source Machine Learning Framework for Everyone
My implementation for the labs of the Neural Networks and Deep Learning course that I studied at my university, Zewail City.
Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).
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