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­­From Y=X to Building a Complete Artificial Neural Network - KDnuggets

­­From Y=X to Building a Complete Artificial Neural Network - KDnuggets : In this tutorial, we will start with the most simple artificial neural network (ANN) and move to something much more complex. We begin by building a machine learning model with no parameters—which is Y=X.

Optimizing the Levenshtein Distance for Measuring Text Similarity - KDnuggets

Optimizing the Levenshtein Distance for Measuring Text Similarity - KDnuggets : For speeding up the calculation of the Levenshtein distance, this tutorial works on calculating using a vector rather than a matrix, which saves a lot of time. We’ll be coding in Java for this implementation.

A Guide to Preparing OpenCV for Android - KDnuggets

A Guide to Preparing OpenCV for Android - KDnuggets : This tutorial guides Android developers in preparing the popular library OpenCV for use. Using a step-by-step guide, the library will be imported into Android Studio and then can be used for performing any of the operations it supports, such as object detection, segmentation, tracking, and more.

Introduction to Federated Learning - KDnuggets

Introduction to Federated Learning - KDnuggets : Federated learning means enabling on-device training, model personalization, and more. Read more about it in this article.

Breaking Privacy in Federated Learning - KDnuggets

Breaking Privacy in Federated Learning - KDnuggets : Despite the benefits of federated learning, there are still ways of breaching a user’s privacy, even without sharing private data. In this article, we’ll review some research papers that discuss how federated learning includes this vulnerability.

Genetic Algorithm (PyGAD) Plays CoinTex Game

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CoinTex is an open-source cross-platform multi-level adventure game developed in Python using Kivy. CoinTex is available for Android at Google Play: https://play.google.com/store/apps/details?id=coin.tex.cointexreactfast&hl=en To pass a level in CoinTex, the player has to collect all the randomly distributed coins while avoiding collision with the monsters and the fires. The monsters are moved randomly. Using only the genetic algorithm (GA) without any machine/deep learning algorithms, a game playing agent is created that plays CoinTex like a professional. The agent is able to stand even in complex levels with many coins, monsters, and fires. The GA is implemented using a Python 3 library named PyGAD. Find its documentation here to get started: https://pygad.readthedocs.io . Install PyGAD using pip: pip install pygad The source code of CoinTex at GitHub: https://github.com/ahmedfgad/CoinTex The source code of the genetic algorithm agent: https://github.com/ahmedfgad/CoinTe...

Ahmed Gad

My profile at KDnuggets.com Ahmed Gad

Feature Reduction using Genetic Algorithm with Python

This tutorial discusses how to use the genetic algorithm (GA) for reducing the feature vector extracted from the Fruits360 dataset in Python mainly using NumPy and Sklearn. Feature Reduction using Genetic Algorithm with Python

Feature Reduction using Genetic Algorithm with Python

This tutorial discusses how to use the genetic algorithm (GA) for reducing the feature vector extracted from the Fruits360 dataset in Python mainly using NumPy and Sklearn. Feature Reduction using Genetic Algorithm with Python

Artificial Neural Networks Optimization using Genetic Algorithm with Python

This tutorial explains the usage of the genetic algorithm for optimizing the network weights of an Artificial Neural Network for improved performance. Artificial Neural Networks Optimization using Genetic Algorithm with Python