Implementation of Artificial Neural Network Algorithm

Overview

Artificial Neural Network

This repository contain implementation of Artificial Neural Network Algorithm in several programming languanges and frameworks. This repository was created to introduce artifical neural network in a simple way. Artificial Neural Network has become popular at this time. This branch field of Artificial Intelligence has given powerful impact to our daily life such as social media recomendation system, face detection of camera on phone and many more. Therefore, to keep up our knowledge in technology especially Artificial Intelligence, we have to understand the concept of Artificial Neural Network.

"AI is the new electricity" -Andrew Ng

Table of Contents

What is ANN?

Artificial Neural Network or simply ANN is one of bio-inspired algorithm that mimicking the work of neural network in brain. Neural network in brain consist of many neuron that will receive and fire electric signal each other. Generally speaking, these neurons have dendrites, cell body, axon, and axon terminals. These neuron receive electrical signal via dendrites then go pass through body cell also called soma which contain nucleus. After the electrical signal pass through the soma, axon will transmit it to axon terminals and the electrical signal will jump over synapses to another neuron. This notion of how neuron work had inspired Warren S. McCulloch and Walter H. Pitts to wrote a paper which titled A Logical Calculus of The Ideas Immanent in Nervous Activity. This paper explained about the early mathematical concept of ANN called artificial neuron or threshold logic unit. This concept develop progressively, from artificial neuron to perceptron then multi layer perceptron. The concept of multi layer perceptron or MLP will lead us to Deep Learning.

alt text

How ANN Works?

So, how does ANN work?

alt text

Owner
Resha Dwika Hefni Al-Fahsi
AI Engineer at Techbros Group
Resha Dwika Hefni Al-Fahsi
PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper.

deep-linear-shapes PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper. If you find this code useful i

Romain Loiseau 27 Sep 24, 2022
πŸ”₯RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds (CVPR 2020) This is the official implementation of RandLA-Net (CVPR2020, Oral

Qingyong 1k Dec 30, 2022
GE2340 project source code without credentials.

GE2340-Project-Public GE2340 project source code without credentials. Run the bot.py to start the bot Telegram: @jasperwong_ge2340_bot If the bot does

0 Feb 10, 2022
Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter

ACE Please find the preliminary version published at BMVC 2020 in the folder BMVC_version, and its extended journal version in Journal_version. Datase

28 Dec 25, 2022
PyTorch implementation of MuseMorphose, a Transformer-based model for music style transfer.

MuseMorphose This repository contains the official implementation of the following paper: Shih-Lun Wu, Yi-Hsuan Yang MuseMorphose: Full-Song and Fine-

Yating Music, Taiwan AI Labs 142 Jan 08, 2023
FluxTraining.jl gives you an endlessly extensible training loop for deep learning

A flexible neural net training library inspired by fast.ai

86 Dec 31, 2022
Complete U-net Implementation with keras

U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The

Sagnik Roy 14 Oct 10, 2022
Official implementation of the NeurIPS 2021 paper Online Learning Of Neural Computations From Sparse Temporal Feedback

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

Lukas Braun 3 Dec 15, 2021
Train neural network for semantic segmentation (deep lab V3) with pytorch in less then 50 lines of code

Train neural network for semantic segmentation (deep lab V3) with pytorch in 50 lines of code Train net semantic segmentation net using Trans10K datas

17 Dec 19, 2022
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning

    VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain

squaresLab 32 Oct 24, 2022
Official implementations of PSENet, PAN and PAN++.

News (2021/11/03) Paddle implementation of PAN, see Paddle-PANet. Thanks @simplify23. (2021/04/08) PSENet and PAN are included in MMOCR. Introduction

395 Dec 14, 2022
This repository contains PyTorch code for Robust Vision Transformers.

This repository contains PyTorch code for Robust Vision Transformers.

117 Dec 07, 2022
ShapeGlot: Learning Language for Shape Differentiation

ShapeGlot: Learning Language for Shape Differentiation Created by Panos Achlioptas, Judy Fan, Robert X.D. Hawkins, Noah D. Goodman, Leonidas J. Guibas

Panos 32 Dec 23, 2022
βœ”οΈ Visual, reactive testing library for Julia. Time machine included.

PlutoTest.jl (alpha release) Visual, reactive testing library for Julia A macro @test that you can use to verify your code's correctness. But instead

Pluto 68 Dec 20, 2022
Material related to the Principles of Cloud Computing course.

CloudComputingCourse Material related to the Principles of Cloud Computing course. This repository comprises material that I use to teach my Principle

Aniruddha Gokhale 15 Dec 02, 2022
Generative Flow Networks for Discrete Probabilistic Modeling

Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo

Narsil-Dinghuai Zhang 51 Dec 20, 2022
[CVPR 2022 Oral] Versatile Multi-Modal Pre-Training for Human-Centric Perception

Versatile Multi-Modal Pre-Training for Human-Centric Perception Fangzhou Hong1  Liang Pan1  Zhongang Cai1,2,3  Ziwei Liu1* 1S-Lab, Nanyang Technologic

Fangzhou Hong 96 Jan 03, 2023
A curated (most recent) list of resources for Learning with Noisy Labels

A curated (most recent) list of resources for Learning with Noisy Labels

Jiaheng Wei 321 Jan 09, 2023
Python library for tracking human heads with FLAME (a 3D morphable head model)

Video Head Tracker 3D tracking library for human heads based on FLAME (a 3D morphable head model). The tracking algorithm is inspired by face2face. It

61 Dec 25, 2022
QICK: Quantum Instrumentation Control Kit

QICK: Quantum Instrumentation Control Kit The QICK is a kit of firmware and software to use the Xilinx RFSoC to control quantum systems. It consists o

81 Dec 15, 2022