Neural Network

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Great Reads

A 3-Layer Feed-Forward Neural Net In C#, with Graphical Display

by Gary.Miller.WPF

MNIST Digit recognition in C#

A Note on Neural Networks

by Dr. Song Li

This is a library to implement Neural Networks in JavaScript.

A Simple and Complete Explanation of Neural Networks

by Mahsa Hassankashi

This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.

A Tic Tac Toe AI with Neural Networks and Machine Learning

by Thomas Daniels

This article describes the making of a tic tac toe player that uses neural networks and machine learning.

Latest Articles

A 3-Layer Feed-Forward Neural Net In C#, with Graphical Display

by Gary.Miller.WPF

MNIST Digit recognition in C#

A Note on Neural Networks

by Dr. Song Li

This is a library to implement Neural Networks in JavaScript.

A Simple and Complete Explanation of Neural Networks

by Mahsa Hassankashi

This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.

A Tic Tac Toe AI with Neural Networks and Machine Learning

by Thomas Daniels

This article describes the making of a tic tac toe player that uses neural networks and machine learning.

All Articles

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neural-network

A 3-Layer Feed-Forward Neural Net In C#, with Graphical Display

by Gary.Miller.WPF

MNIST Digit recognition in C#

A Note on Neural Networks

by Dr. Song Li

This is a library to implement Neural Networks in JavaScript.

A Simple and Complete Explanation of Neural Networks

by Mahsa Hassankashi

This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.

A Tic Tac Toe AI with Neural Networks and Machine Learning

by Thomas Daniels

This article describes the making of a tic tac toe player that uses neural networks and machine learning.

Age Estimation With Deep Learning: Building CNN

by Sergey L. Gladkiy

In this article we’ll build the network we’ve designed using the Keras framework.

Age Estimation With Deep Learning: Designing CNN

by Sergey L. Gladkiy

In this article we’ll guide you through one of the most difficult steps in the DL pipeline: the CNN design.

Age Estimation With Deep Learning: Training CNN

by Sergey L. Gladkiy

In this article we train the CNN for age estimation.

Age Estimation With Deep Learning: Using CNN to Predict Age

by Sergey L. Gladkiy

In this article we will explain how to use the pre-trained CNN for estimating a person’s age from an image.

AI Anomaly Detection on Bitcoin Time Series Data

by Sergio Virahonda

In this article we talk about anomaly detection on time series data.

AI Chatbots With TensorFlow.js: Improved Trivia Expert

by Raphael Mun

In this article we will create a knowledge chatbot.

AI Forecasting and Anomaly Detection on Streaming Bitcoin Prices

by Sergio Virahonda

In this article we’ll combine forecasting and detection on a live stream of Bitcoin price data.

AI Forecasting on Bitcoin Time Series Data

by Sergio Virahonda

In the next article, we are going to discuss forecasting on Bitcoin time series.

AI Image Classification on iOS with ResNet

by Jarek Szczegielniak

Having converted a ResNet model to the Core ML format in the previous article, in this article we’ll now use it in a simple iOS application.

AI Queue Length Detection: Counting the Number of People in an Area

by MehreenTahir

In this article, we will train a deep learning model to detect and count the number of people in a given area.

AI Queue Length Detection: Object detection using Keras

by MehreenTahir

This is the first in an article series where we’re going to show how to make an AI queue length detector.

AI Queue Length Detection: R-CNN for Custom Object Detection Using Keras

by MehreenTahir

In this article, we’ll explore some other algorithms used for object detection and will learn to implement them for custom object detection.

AI: Genetic Evolution of Virtual Fish

by hemanthk119

Genetic Mutations of Neural Networks to produce better offspring in fish like virtual creatures

Android Arm NN Image Classification

by Joel Ivory Johnson

Image classification using Arm NN on Android mobile devices

Android Tensorflow Lite Best Practices and Optimizations

by Joel Ivory Johnson

In this article we will consider the ways in which the network could be further optimized.

ANNT: Feed Forward Fully Connected Neural Networks

by Andrew Kirillov

The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.

ANNT: Recurrent Neural Networks

by Andrew Kirillov

Use of ANNT library to create recurrent ANNs and apply them to different tasks

Artificial Neural Network C++ Class

by Hatem Mostafa

Artificial Neural Network C++ class with two use cases: Counter and Handwritten Digits recognition

Automatic Trash Classification with Raspberry Pi and Arm NN Machine Learning

by Dawid Borycki

In this article, we'll demonstrate building an Arm NN-based application for an IoT device that can perform automatic trash sorting through image analysis.

Basic Artificial Neural Network in C#

by Bhairav Thakkar

A basic artificial neural network code for experimenting

Basis of Neural Networks in Visual Basic .NET

by Emiliano Musso

Basics of implementing a neural network in VB.NET

Build Simple AI .NET Library - Part 3 - Perceptron

by Gamil Yassin

Perceptron, when to use it and sample code

Build Simple AI .NET Library - Part 4 - Beyond Perceptron

by Gamil Yassin

Part 4 of a series of articles demonstrating .NET AI library from scratch

Build Simple AI .NET Library - Part 5 - Artificial Neural Networks

by Gamil Yassin

Types of Artificial Neural Networks

Building a Core ML Pipeline for the iOS Vision Framework

by Jarek Szczegielniak

In this article we’ll create a Core ML pipeline to be our end-to-end model.

Building a Mobile Style Transfer CycleGAN with Keras

by Abdulkader Helwan

In this article, we implement a CycleGAN from scratch.

Building a Style Transfer CycleGAN from Scratch

by Abdulkader Helwan

In this article, we implement a CycleGAN with a residual-based generator.

Building an AI Image Classification Model for iOS Using Create ML and Core ML

by Jarek Szczegielniak

In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.

Building an Object Detection iOS App with YOLO Core ML Model

by Jarek Szczegielniak

In this last article in this series, we’ll extend the application to use our YOLO v2 model for object detection.

Cartpole: The “Hello World” of Reinforcement Learning

by philoxenic

In this article, you will be up and running, and will have done your first piece of reinforcement learning.

Cartpole: Tweaking the Options

by philoxenic

In this article, we will see what’s going on behind the scenes and what options are available for changing the reinforcement learning.

Cat or Not - An Image Classifier using Python and Keras

by Ryan Peden

A code-first introduction to neural networks

Competing on kaggle.com for the First Time

by Philipp_Engelmann

Competing on kaggle.com for the first time

Converting an ONNX Object Detection Model to iOS Core ML

by Jarek Szczegielniak

In this series, we’ll use a pretrained model to create an iOS application that will detect multiple persons and objects in a live camera feed rather than in a static picture.

Converting ONNX Image Classification Models to Core ML

by Jarek Szczegielniak

In this article we'll convert a ResNet model to the Core ML format.

Creating a Text-to-speech engine with Google Tesseract and Arm NN on Raspberry Pi

by Dawid Borycki

How to choose and convert an existing TensorFlow model to work with Arm NN and best practices for model conversion and implementing Arm NN solutions.

Creating a Turing Machine in Python – Part 1

by Philipp_Engelmann

In this series, I want to show you how to create a simple console-based Turing machine in Python. You can check out the full source code on https://github.com/phillikus/turing_machine. In this part, I will explain the fundamental theory behind Turing machines and set up the project based on that.

Creating a Turing Machine in Python – Part 2

by Philipp_Engelmann

How to create a Turing machine in Python - Part 2

Creating a YOLO Core ML Object Detector with Decoding Logic

by Jarek Szczegielniak

In this article we are ready to include detection decoding directly in the Core ML model.

Creating an Android AI App With Tensorflow Lite

by Joel Ivory Johnson

In this article we will create an Android application and import our TensorFlow Lite model into it.

Data Mining: An Introduction to Neural Networks in SQL Server

by Harinder Saluja

Implement Neural Network in SQL Server

Decoding a Core ML YOLO Object Detector

by Jarek Szczegielniak

In this article, we will decode the Core ML YOLO Model by transforming an array of abstract numbers to a human-readable form.

Decoding a YOLO Core ML Object Detector Using Array Operations

by Jarek Szczegielniak

In the next article, we’ll do the same but with array operations. This will allow us to include the decoding logic directly in the model.

Deep Learning in C#: Coin Recognition in Keras.NET, Part I

by Arnaldo P. Castaño

In this article, we will examine a convolutional neural network for the problem of coin recognition, and we will implement one in Keras.NET.

Deep Learning in C#: Coin Recognition in Keras.NET, Part II

by Arnaldo P. Castaño

In this article we will examine the CNN we implemented for coin recognition using Keras.NET.

Deep Learning in C#: Coin Recognition with a Pre-Trained Model in ML.NET

by Arnaldo P. Castaño

To end off this series, we will present the alternative of adapting a pre-trained CNN to the coin recognition problem we have been examining all along.

Deep Learning in C#: Understanding Neural Network Architecture

by Arnaldo P. Castaño

In this article we will go over the basics of supervised machine learning and what the training and verification phases consist of.

Detecting Pests Using Pre-Trained SSD Models

by Sergey L. Gladkiy

In the next article, we’ll use a pre-trained DNN to detect pests on video.

Detecting Pests with a Motion Detector and Trained DNN

by Sergey L. Gladkiy

In this article, we’ll show you how to develop a simple motion detector and combine it with the trained DNN model to detect moose on video.

Detecting Unusual Pests

by Sergey L. Gladkiy

In this we’ll talk about some ideas for detecting "exotic" pests, such as moose and armadillos.

Eliminating Pests with a Raspberry Pi

by Sergey L. Gladkiy

In this article, we’ll test our detection algorithm on a Raspberry Pi 3 device and create the "scare pests away" part of our pest eliminator by playing a loud sound.

Extending Dataset with Data Augmentation

by Sergey L. Gladkiy

In this article, we’ll see how the same result can be achieved by data augmentation.

Fine-tuning VGG16 to Classify Clothing

by Abdulkader Helwan

In this article we show you how to train VGG19 to recognize what people are wearing.

From Stationarity to Randomness through Chaos

by Miguel Diaz Kusztrich

Using R to explore complexity of time series generated by simple process

Generate New Fashion Designs with a Generative Adversarial Network (GAN)

by Abdulkader Helwan

In this article we show you how to build a Generative Adversarial Network (GAN) for fashion design generation.

Getting Started With Deep Learning in Your Browser Using TensorFlow.js

by Raphael Mun

In this article, I will show you how quickly and easily set up and use TensorFlow.js to train a neural network to make predictions from data points.

Handwritten Digits Reader UI

by KristianEkman

A C# object oriented Neural Network, trainer, and Windows Forms user interface for recognitions of hand-written digits.

Hybrid Edge AI for Facial Recognition: Next Steps

by Sergey L. Gladkiy

In this article, we’ll discuss some aspects of developing a facial recognition system from scratch.

Image Classification Using Neural Networks in .NET

by hemanthk119

Image Classification implementation using Deep Belief Networks and Convolutional Neural Networks in .NET

Image Tagger - A Convolutional Neural Network Based Image Classifier

by Huseyin Atasoy

An image classifier / tagger based on convolutional neural networks. Now more than 10 times faster with the Intel MKL support.

Implementation of Convolutional Neural Network using Python and Keras

by Nikola M. Živković

Implementation of Convolutional Neural Network using Python and Keras

Input Normalization as Separate Layer in CNTK with C#

by Bahrudin Hrnjica

How to implement data normalization as regular neural network layer, which can simply training process and data preparation

Introduction to Keras

by Thomas Daniels

In this article, let’s dive into Keras, a high-level library for neural networks.

Introduction to OpenAI Gym: Atari Breakout

by philoxenic

In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.

iOS Object Detection with Live Camera Preview

by Jarek Szczegielniak

In the next article, we’ll start working on the iOS application that will use that model.

Learning Breakout From RAM – Part 1

by philoxenic

In this article we will learn from the contents of the game’s RAM instead of the pixels.

Learning Breakout From RAM – Part 2

by philoxenic

In this article, we will see how we can improve by approaching the RAM in a slightly different way.

Learning Breakout More Quickly

by philoxenic

In this article, we will see how you can use a different learning algorithm (plus more cores and a GPU) to train much faster on the mountain car environment.

Learning Breakout: Advanced Topics

by philoxenic

In this final article in this series, we will look at slightly more advanced topics: minimizing the "jitter" of our Breakout-playing agent, as well as performing grid searches for hyperparameters.

Learning Machine Learning, Part 2: Algorithms and Techniques

by Alibaba Cloud

In this post, we learn about algorithms that help implement ML functions.

Logo Recognition System

by Ammar Albush 1997

Logo Recognition System Program written in C# .NET 6.0 Windows Form (Tensorflow.net,Tensorflow.keras,Emgu Cv,ScottPlot.WinForms,Newtonsoft.Json)

Multiple convolution neural networks approach for online handwriting recognition

by Vietdungiitb

The research focuses on the presentation of word recognition technique for an online handwriting recognition system which uses multiple component neural networks (MCNN) as the exchangeable parts of the classifier.

Number Recognition with MLP Neural Network

by mohammad farahi

English Number recognition with Multi Layer Perceptron Neural Network (MLP)

Preparing Data for AI Fashion Classification

by Abdulkader Helwan

In this article we’ll show you how to use transfer learning to fine-tune the VGG19 model to classify fashion clothing categories.

Preparing Data for AI Image Classification on iOS

by Jarek Szczegielniak

In this article we’ll start data preparation for this new, custom model, to be later trained using the Create ML framework.

Preparing Dataset

by Sergey L. Gladkiy

In this article we’ll create the training dataset for our pest of choice: The moose.

Preprocessing Time Series Data for AI Forecasting and Anomaly Detection

by Sergio Virahonda

In this article, we learn how to prepare time series data to be fed to machine learning (ML) and deep learning (DL) models.

Real-time AI Person Detection on Edge Devices: Detecting Persons on Video in Real-time Mode

by Sergey L. Gladkiy

In this article, we’ll modify the code for real-time processing on an edge device.

Real-time AI Person Detection on Edge Devices: Detecting Persons Using Pre-trained SSD Models

by Sergey L. Gladkiy

In this article, we’ll showcase the Python code for launching these models and detect humans in images.

Real-time AI Person Detection on Edge Devices: Getting Started

by Sergey L. Gladkiy

This is the first in an article series where we’ll show you how to detect people in real time (or near-real time) on Raspberry Pi.

Real-time AI Person Detection on Edge Devices: Launching SSD on Raspberry Pi

by Sergey L. Gladkiy

In this article, we’ll see how you can install Python-OpenCV on the device and run the code.

Real-time AI Person Detection on Edge Devices: Testing SSD Models on Raspberry Pi

by Sergey L. Gladkiy

In this article, we’ll test the accuracy and the performance of the MibileNet and SqueezeNet models on the Raspberry Pi device.

Real-time AI Pest Elimination on Edge Devices: Getting Started

by Sergey L. Gladkiy

In this article, we compared two DNN types we can use to detect pests: detectors and classifiers.

Reducing Packing Overhead in Matrix-Matrix Multiplication

by Intel

Improve Performance on Multicore and Many-Core Intel® Architectures, Particularly for Deep Neural Networks

ReInventing Neural Networks

by Byte-Master-101

Neural Networks can do a lot of amazing things, and you can understand how you can make one from the ground up. You can actually be surprised how easy it is to develop one from scratch!

ReInventing Neural Networks - Part 2

by Byte-Master-101

In Part 2, the Neural Network made in Part 1 is tested in an environment made in Unity so that we can see how well it performs.

ReInventing Neural Networks - Part 3

by Byte-Master-101

Now that we got the basics over with, it's time for improvement!

Running AI Fashion Classification on Real Data

by Abdulkader Helwan

In this article we evaluate VGG19 using real images taken by a phone camera.

Setting Up an Android AI Development Environment

by Joel Ivory Johnson

This is the first in a series of articles on using TensorFlow Lite on Android to bring the power of machine learning and deep neural networks to mobile application

Setting up macOS for ML and AI Development

by Jarek Szczegielniak

In this article we prepare our development environment.

The Histogram Neuron - A Solution for "Kitten Stew" in Image Classification with CNNs

by R. Stacy Smyth

Approach I used to get the CNN to behave in a more intuitively sensible way

The Math behind Neural Networks: Part 1 - The Rosenblatt Perceptron

by Serge Desmedt

A try it yourself guide to the basic math behind perceptrons

The Math behind Neural Networks: Part 2 - The ADALINE Perceptron

by Serge Desmedt

A try it yourself guide to the basic math behind ADALINE perceptron

Training a DNN

by Sergey L. Gladkiy

In this article, we’ll discuss training our DNN classifier with the augmented dataset.

Training a Running a Deep CycleGAN for Mobile Style Transfer

by Abdulkader Helwan

In this article, we train a CycleGAN with a U-Net-based generator.

Training and Running a GAN for Fashion Design Generation

by Abdulkader Helwan

In this article we show you how to train the GAN for fashion design generation.

Training Your Own TensorFlow Neural Network For Android

by Joel Ivory Johnson

In this article we will generate output from a program will provide a TensorFlow freeze graph ready to be used or converted to TensorFlow Lite.

Using an ONNX Neural Network Model with TensorFlow Lite on Android

by Joel Ivory Johnson

In this article we will take a pre-trained neural network and adapt it for use in TensorFlow Lite.

Using CycleGAN for Mobile Style Transfer

by Abdulkader Helwan

In this article, we discuss the CycleGAN architecture.

Using Portable ONNX AI Models in Java

by Keith Pijanowski

In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.

Using Portable ONNX AI Models in Python

by Keith Pijanowski

In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.

Visualizing TensorFlow Lite AI Results on Android

by Joel Ivory Johnson

In the previous installation of this series, a TensorFlow Lite interpreter had examined an image and produced its output. In this article we learn how to interpret these results and create visualizations for them.