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

Abstract: In recent years, neural network models have been widely used in many tasks, however, tampering operations from malicious attackers, e.g., backdoor attacks and parameter malicious tampering, ...

The current machine_learning directory in TheAlgorithms/Python lacks implementations of neural network optimizers, which are fundamental to training deep learning models effectively. To fill this gap ...

3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

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 ...

Abstract: Among the various control strategies for complex dc–dc converters, those employing neural networks have risen to prominence. They excel in their ability to approximate functions without the ...

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 ...