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Neural Networks

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by Hatem Mostafa
Artificial Neural Network C++ class with two use cases: Counter and Handwritten Digits recognition
by Serge Desmedt
A try it yourself guide to the basic math behind perceptrons
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.
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.

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by Hatem Mostafa
Artificial Neural Network C++ class with two use cases: Counter and Handwritten Digits recognition
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)
by Tejpal Singh Chhabra
A C++ class implementing a back-propagation algorithm neural net, that supports any number of layers/neurons
by Denis Pashkov
Solve XOR problem using dynamic weights

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Neural Networks 

13 Nov 2023 by Hatem Mostafa
Artificial Neural Network C++ class with two use cases: Counter and Handwritten Digits recognition
12 May 2019 by Serge Desmedt
A try it yourself guide to the basic math behind perceptrons
19 Feb 2018 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.
28 Sep 2018 by Andrew Kirillov
The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.
8 Jan 2019 by KristianEkman
A C# object oriented Neural Network, trainer, and Windows Forms user interface for recognitions of hand-written digits.
24 Jun 2019 by Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.
16 Sep 2017 by Gamil Yassin
Perceptron, when to use it and sample code
17 Sep 2017 by Gamil Yassin
Part 4 of a series of articles demonstrating .NET AI library from scratch
3 Nov 2018 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.
20 Aug 2020 by Serge Desmedt
A try it yourself guide to the basic math behind ADALINE perceptron
22 Nov 2018 by Philipp_Engelmann
How to create a Turing machine in Python - Part 2
26 Jun 2019 by hemanthk119
Image Classification implementation using Deep Belief Networks and Convolutional Neural Networks in .NET
26 Feb 2021 by Sergio Virahonda
In this article we talk about anomaly detection on time series data.
5 Mar 2018 by Nikola M. Živković
Implementation of Convolutional Neural Network using Python and Keras
21 Nov 2020 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.
5 Oct 2020 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.
26 Aug 2020 by Jarek Szczegielniak
In this article we prepare our development environment.
1 Sep 2020 by Jarek Szczegielniak
In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.
16 Sep 2020 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
7 Oct 2020 by Sergey L. Gladkiy
In this article, we’ll showcase the Python code for launching these models and detect humans in images.
4 Nov 2020 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.
23 Dec 2020 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.
22 Nov 2016 by Miguel Diaz Kusztrich
Using R to explore complexity of time series generated by simple process
30 Apr 2019 by Apriorit Inc, Semyon Boyko
The approach that allows you to make a neural network analyze the current frame while remembering the state of previous frames
8 Jul 2020 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.
27 Oct 2020 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.
25 Feb 2021 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.
18 Mar 2021 by Abdulkader Helwan
In this article we evaluate VGG19 using real images taken by a phone camera.
26 Jun 2020 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.
29 Jun 2020 by philoxenic
In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.
30 Jun 2020 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.
2 Jul 2020 by philoxenic
In this article we will learn from the contents of the game’s RAM instead of the pixels.
22 Jul 2020 by Sergey L. Gladkiy
In this article we’ll build the network we’ve designed using the Keras framework.
23 Jul 2020 by Sergey L. Gladkiy
In this article we train the CNN for age estimation.
27 Aug 2020 by Jarek Szczegielniak
In this article we'll convert a ResNet model to the Core ML format.
28 Aug 2020 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.
31 Aug 2020 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.
18 Sep 2020 by Joel Ivory Johnson
In this article we will create an Android application and import our TensorFlow Lite model into it.
9 Oct 2020 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.
28 Oct 2020 by MehreenTahir
In this article, we will train a deep learning model to detect and count the number of people in a given area.
6 Nov 2020 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.
6 Nov 2020 by Arnaldo P. Castaño
In this article we will examine the CNN we implemented for coin recognition using Keras.NET.
23 Nov 2020 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.
26 Nov 2020 by Jarek Szczegielniak
In this article we’ll create a Core ML pipeline to be our end-to-end model.
3 Mar 2021 by Sergey L. Gladkiy
In this article, we compared two DNN types we can use to detect pests: detectors and classifiers.
16 Dec 2020 by Sergey L. Gladkiy
In the next article, we’ll use a pre-trained DNN to detect pests on video.
17 Dec 2020 by Sergey L. Gladkiy
In this we’ll talk about some ideas for detecting "exotic" pests, such as moose and armadillos.
21 Dec 2020 by Sergey L. Gladkiy
In this article, we’ll see how the same result can be achieved by data augmentation.
22 Dec 2020 by Sergey L. Gladkiy
In this article, we’ll discuss training our DNN classifier with the augmented dataset.
24 Dec 2020 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.
16 Mar 2021 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.
17 Mar 2021 by Abdulkader Helwan
In this article we show you how to train VGG19 to recognize what people are wearing.
22 Mar 2021 by Abdulkader Helwan
In this article we show you how to train the GAN for fashion design generation.
27 Dec 2017 by R. Stacy Smyth
Approach I used to get the CNN to behave in a more intuitively sensible way
13 Jul 2018 by Bahrudin Hrnjica
How to implement data normalization as regular neural network layer, which can simply training process and data preparation
25 Jan 2019 by Philipp_Engelmann
Competing on kaggle.com for the first time
21 Jul 2020 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.
11 Sep 2020 by Keith Pijanowski
In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.
23 Sep 2020 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.
8 Oct 2020 by Sergey L. Gladkiy
In this article, we’ll see how you can install Python-OpenCV on the device and run the code.
14 Oct 2020 by Sergey L. Gladkiy
In this article, we’ll modify the code for real-time processing on an edge device.
24 Nov 2020 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.
25 Nov 2020 by Jarek Szczegielniak
In this article we are ready to include detection decoding directly in the Core ML model.
27 Nov 2020 by Jarek Szczegielniak
In the next article, we’ll start working on the iOS application that will use that model.
30 Nov 2020 by Jarek Szczegielniak
In this last article in this series, we’ll extend the application to use our YOLO v2 model for object detection.
2 Mar 2021 by Sergio Virahonda
In this article we’ll combine forecasting and detection on a live stream of Bitcoin price data.
19 Mar 2021 by Abdulkader Helwan
In this article we show you how to build a Generative Adversarial Network (GAN) for fashion design generation.
4 Apr 2019 by Apriorit Inc, Semyon Boyko
Find out an easy way to use the pretrained Inception V3 neural network for video classification.
3 Jul 2020 by philoxenic
In this article, we will see how we can improve by approaching the RAM in a slightly different way.
6 Jul 2020 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.
14 Sep 2020 by Keith Pijanowski
In this article, I provided a brief overview of the ONNX Runtime and the ONNX format.
17 Sep 2020 by Joel Ivory Johnson
In this article we will take a pre-trained neural network and adapt it for use in TensorFlow Lite.
21 Sep 2020 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.
22 Sep 2020 by Joel Ivory Johnson
In this article we will consider the ways in which the network could be further optimized.
26 Oct 2020 by MehreenTahir
This is the first in an article series where we’re going to show how to make an AI queue length detector.
9 Nov 2020 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.
15 Jun 2021 by Abdulkader Helwan
In this article, we discuss the CycleGAN architecture.
17 Jun 2021 by Abdulkader Helwan
In this article, we train a CycleGAN with a U-Net-based generator.
18 Jun 2021 by Abdulkader Helwan
In this article, we implement a CycleGAN with a residual-based generator.
7 Feb 2017 by Intel
Improve Performance on Multicore and Many-Core Intel® Architectures, Particularly for Deep Neural Networks
16 Jun 2021 by Abdulkader Helwan
In this article, we implement a CycleGAN from scratch.
10 Oct 2018 by Dr. Song Li
This is a library to implement Neural Networks in JavaScript.
3 Apr 2019 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.
8 Sep 2015 by Emiliano Musso
Basics of implementing a neural network in VB.NET
11 May 2020 by Huseyin Atasoy
An image classifier / tagger based on convolutional neural networks. Now more than 10 times faster with the Intel MKL support.
9 Apr 2013 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.
7 Aug 2017 by Bhairav Thakkar
A basic artificial neural network code for experimenting
24 May 2017 by mohammad farahi
English Number recognition with Multi Layer Perceptron Neural Network (MLP)
28 Jan 2016 by hemanthk119
Genetic Mutations of Neural Networks to produce better offspring in fish like virtual creatures
1 Mar 2021 by Sergio Virahonda
In the next article, we are going to discuss forecasting on Bitcoin time series.
1 Mar 2018 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!
24 Jul 2020 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.
22 Jun 2020 by Thomas Daniels
In this article, let’s dive into Keras, a high-level library for neural networks.
28 Mar 2023 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)
20 Dec 2018 by Andrew Kirillov
Use of ANNT library to create recurrent ANNs and apply them to different tasks
4 Sep 2022 by Tejpal Singh Chhabra
A C++ class implementing a back-propagation algorithm neural net, that supports any number of layers/neurons
13 Feb 2017 by Alibaba Cloud
In this post, we learn about algorithms that help implement ML functions.