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Best AI and data science courses for workflow automation

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.
IEEE

A Survey on Neural Network Prediction Based on Fuzzy Information Granules: Methods, Applications and Future Challenges

Abstract: In the era of artificial intelligence, the complexity and diversity of data have posed unprecedented challenges for prediction tasks. Fuzzy information granules (FIGs) have emerged as a ...
eLife

Pupil dilation offers a time-window on prediction error

Pupil dilation provides a physiological readout of information gain during the brain's internal process of belief updating in the context of associative learning.
Opinion

Data 2026 outlook: The rise of semantic spheres of influence

As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large. Some accounts estimate that AI is driving 90% of US GDP growth, while others ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Slate

CNN Is Using an Election Polling Tool That Anyone Can Rig

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. By mid-October, the Democrats’ chances ...
GitHub

0xnightfly/crypto-price-predictor-updated

A comprehensive AI-powered system for predicting volatility, skewness, and kurtosis of cryptocurrency and commodity price changes using PyTorch neural networks. Designed for Monte Carlo simulation ...
C&EN

Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials

Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States Department of Chemistry, Carnegie Mellon University, 5000 ...
IEEE

Hypergraph Neural Networks Based on Enclosing Subgraph Extraction for Temporal Link Prediction

Abstract: The Graph Neural Network (GNN) methods based on enclosing subgraph extraction have achieved excellent results in static graph link prediction tasks. However, most real-world networks are ...
C&EN

Multilevel Fusion Graph Neural Network for Molecule Property Prediction

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...
Frontiers

Prediction of mechanical properties of steel fibre-reinforced concrete under elevated temperature using artificial neural network techniques (ann)

Department of Civil Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India This study investigates the mechanical performance of ...
GitHub

GitHub - moreira-and/time-series-prediction-rnn: Practical project for time series prediction using recurrent neural networks (RNN) with Python.

This project implements a robust time series forecasting pipeline to predict the closing prices of the IBOVESPA index, Brazil’s main stock market benchmark. It combines advanced data preprocessing ...