Learn With Jay on MSNOpinion

Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...
Tech Xplore

AI models stumble on basic multiplication without special training methods, study finds

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...
Science Focus

We might finally know what will burst the AI bubble

The current boom in AI technology has ridden on a wave known as ‘deep learning’, which is an approach to creating intelligent ...
IEEE

Improved Deep Learning-Based Microwave Inversion With Experimental Training Data

Abstract: Deep learning-based inversion methods show great promise. The most common way to develop deep learning inversion techniques is to use synthetic (i.e., computationally-generated) data for ...
Analytics Insight

What are the Best Python Libraries for Reinforcement Learning in 2025?

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
IEEE

A Collaborative Multi-Agent Deep Reinforcement Learning-Based Wireless Power Allocation With Centralized Training and Decentralized Execution

Abstract: Despite the success of Deep Reinforcement Learning (DRL) in radio-resource management within multi-cell wireless networks, applying it to power allocation in ultra-dense 5G and beyond ...