Credit Card Fraud Detection using Graph Neural Networks
Credit card fraud detection in transactions is a critical application where Graph Neural Networks (GNNs) and Graph Representation Learning can be utilized to improve accuracy and efficiency. In this scenario, credit card transactions can be represented as a graph, where…
Smart Basketball Tech: Score Tracking & Player Analysis
Tracking basketball players and the ball during a game is a challenging but smart basketball tech is a rewarding task that can provide valuable insights for both score counting and player performance analysis. Computer vision techniques, including object detection and…
Traffic Flow Forecasting by attention mechanism with ST-GCNs
The use of deep learning techniques, namely Spatial-Temporal Graph Convolutional Networks (ST-GCNs) enhanced with attention mechanisms, for traffic flow forecasting. In transportation and urban planning, traffic flow forecasting is a crucial task. It attempts to forecast future traffic conditions based…
How to do Bitcoin Network Anomaly Detection via GNNs?
Identifying possible money-laundering users through Bitcoin Network Anomaly Detection via Graph Neural Networks is an essential task for preserving the integrity of the cryptocurrency ecosystem. For such tasks, graph neural networks, or GNNs, hold great promise because they are able…
How To Setup Top-View Health Monitoring For Poultry Farms
For poultry farmers to ensure their chickens’ welfare and productivity, health monitoring is essential. Using movement analysis from a top-view camera is one efficient method. This entails monitoring the hens’ behaviors and movement patterns, which can reveal information about their…
Industry 4.0 and its Impact on Manufacturing using AI
An unprecedented era of manufacturing innovation has begun with the convergence of Industry 4.0 and artificial intelligence (AI). This era brings with it unprecedented levels of automation, efficiency, and flexibility. Now, this article examines the mutually beneficial relationship between Industry…
How to do Decision Tree Classification with Python Scikit?
A straightforward but powerful machine learning method for regression and classification is the decision tree. The structure resembles a tree, with leaf nodes signifying predictions or outcomes, branches representing decision rules, and core nodes representing features or attributes. Decision trees…
What are Decision Trees in Artificial Intelligence?
A simple yet powerful machine learning method for regression and classification applications is the decision tree. The structure resembles a tree, with leaf nodes signifying predictions or outcomes, branches representing decision rules, and core nodes representing features or attributes. Decision…
How to implement Random Forest Classifier with Scikit-Learn?
Random Forest is a popular ensemble machine-learning technique used in regression and classification applications. Its premise is bagging, or bootstrap aggregating, and it makes predictions by using multiple decision trees.The algorithm was first presented by Adele Cutler and Leo Breiman….
A Simple Into to Random Forest Algorithm in Machine Learning
Random Forest is a popular ensemble machine-learning technique used in regression and classification applications. Its premise is bagging, or bootstrap aggregating, and it makes predictions by using multiple decision trees. The algorithm was first presented by Adele Cutler and Leo…