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Artificial Intelligence 

Machine Learning Basics and Perceptron Learning Algorithm
22 Oct 2017 by Shun Huang
Machine learning is a term that people are talking about often in the software industry, and it is becoming even more popular day after day. Media is filled with many fancy machine learning related words: deep learning, OpenCV, TensorFlow, and more.
artificial-intelligence
neural-network
machine-learning
OpenCV
Data Visualization – Insights with Matplotlib
3 Oct 2020 by Sandeep Mewara
A detailed look at how to deduce insights using Matplotlib with real world examples.
Python
artificial-intelligence
machine-learning
Neural Network Learning by the Levenberg-Marquardt Algorithm with Bayesian Regularization (part 1)
25 Feb 2010 by César de Souza
A complete explanation for the totally lost, part 1 of 2. The Levenberg–Marquardt algorithm provides a numerical solution to the problem of minimizing a (generally nonlinear) function. This article shows how the Levenberg-Marquart can be used to train Neural Networks.
C#
.NET
artificial-intelligence
Common Neural Network Activation Functions
24 Nov 2017 by Nikola M. Živković
Common neural network activation functions
artificial-intelligence
machine-learning
neural-network
Injecting intelligence – Building apps using Microsoft Cognitive Services
10 Jul 2016 by Simon Jackson
Technology it seems is moving ever faster and faster, especially in the world of Artificial Intelligence and Machine Learning.  Barriers to entry are breaking down and huge cloud offerings from all the major suppliers are popping up left right and center.  We see these on our devices (Siri, Cortana,
C++
Windows
artificial-intelligence
QA
machine-learning
Malware for Neural Networks: Let’s Get Hacking!
24 Mar 2017 by Rob Kraft
An overview of the techniques that can be used to damage the most popular AI in use today, neural networks
artificial-intelligence
machine-learning
neural-network
Computer Engineering and the Hidden Neural network brain in the Arduino 101
21 Oct 2016 by marcus obrien
Computer engineering and the hidden neural network brain in the Arduino 101
artificial-intelligence
neural-network
machine-learning
microcontroller
Learning React? Start Small.
20 Jun 2017 by Dave Ceddia
If you are learning React, start small
artificial-intelligence
machine-learning
neural-network
Why Computers Haven't Replaced Programmers
17 Dec 2014 by Paul M Watt
Why computers haven't replaced programmers
artificial-intelligence
All-Topics
Hopfield Neural Network for Character Recognition in .NET and C#
7 Aug 2017 by John Newcombe
Hopfield Neural Network for Character Recognition in .NET and C#
C#
.NET
artificial-intelligence
How to Setup Learning Rate Per Iteration in CTNK using C#
22 Nov 2017 by Bahrudin Hrnjica
How to setup learning rate per iteration in CTNK using C#
C#
artificial-intelligence
machine-learning
neural-network
A* Search - An Extension of Dijkstra's Algorithm
21 Jul 2021 by rtybase
Build Recap
3 Apr 2016 by Bill Wagner
Function Optimization with Genetic Algorithm by using GPdotNET
28 Mar 2013 by Bahrudin Hrnjica
Function optimization with genetic algorithm by using GPdotNET
C#
artificial-intelligence
Unity AI Programming Essentials–A Review
10 Jan 2015 by Simon Jackson
A review of Unity AI programming essentials
C#
Unity3D
artificial-intelligence
game
The “War Game” and Understanding Complex Application Development
7 Jul 2016 by Steve Naidamast
Author’s Note… Please note that the use of the words game, war game, and simulation are all used interchangeably through this paper.
artificial-intelligence
STL
How do Artificial Neural Networks learn?
21 Jan 2018 by Nikola M. Živković
The biggest power of ANNs is that they can be familiarized with some kind of problem in the process of training and are later able to solve problems of the same class – just like humans do! But how do they do that?
artificial-intelligence
machine-learning
neural-network
Introduction to Artificial Neural Networks
15 Nov 2017 by Nikola M. Živković
Did you know that first ideas revolving around AI can be traced back to the 40's? Nevertheless, it is still a field that is in its infancy, so to say, and a concept that we still don't know a lot about.
artificial-intelligence
machine-learning
neural-network
Deep Learning – Training an AI to Play Doom
1 Mar 2018 by Philipp_Engelmann
With recent scientific advancements in Deep Learning, Artificial Intelligence and Neural Networks, as well as steadily evolving tools such as Tensorflow, Pytorch, and Keras, writing, testing and optimizing your own Neural Networks is now easier than ever before.
CUDA
Python
artificial-intelligence
neural-network
machine-learning
algorithm
Backpropagation Algorithm in Artificial Neural Networks
23 Jan 2018 by Nikola M. Živković
The Dark Arts: Game Development & the State of the Gaming Industry
19 Jul 2016 by Steve Naidamast
The State of the Industry  One of the most alluring aspects of software development is the creation of one’s own game or a utility to support a game genre.
artificial-intelligence
STL
Quick Look into Machine Learning Workflow
18 Dec 2020 by Sandeep Mewara
A quick look into basic workflow when we apply Machine Learning to a problem
Python
artificial-intelligence
machine-learning
data
A Look At The Growing Need For Anti-virus Software
28 Apr 2012 by snorkie
This paper explores what a virus is, their evolution, and where they may be encountered today.
artificial-intelligence
SysAdmin
Dev
K-Means Clustering Algorithm
8 Aug 2012 by rtybase
This post is dedicated to K-Means Clustering Algorithm, used for unsupervised learning.
artificial-intelligence
machine-learning
Creating a Turing Machine in Python – Part 3
22 Dec 2017 by Philipp_Engelmann
In this part of this series, we will add some more Turing machines and extend the logging.
artificial-intelligence
machine-learning
neural-network
Is software development too complex today ?
19 Feb 2013 by Chris Boss
Today's development tools are becoming so complex that it makes one wonder, what has happened to software development.
Windows
artificial-intelligence
Dev
Machine Learning Basics: Pocket Learning Algorithm and Basic Feature Engineering
12 Feb 2018 by Shun Huang
In the previous article, Machine Learning Basics and Perceptron Learning Algorithm, the assumption was that the Iris Data Set trained by Perceptron Learning Algorithm is linear separable, so the number of misclassification on each training iteration eventually converge to 0.
artificial-intelligence
machine-learning
neural-network


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