According to MarketsandMarkets™, the Smart Learning Market is projected to grow from USD 80.69 billion in 2025 and to reach ...

This paper represents a valuable contribution to our understanding of how LFP oscillations and beta band coordination between the hippocampus and prefrontal cortex of rats may relate to learning.

This important study employs a closed-loop, theta-phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats and reports that disrupting theta-timescale ...

Abstract: Deep reinforcement learning (DRL) is a promising way to develop autonomous driving decision-making models. However, poor driving decisions and low sample efficiency for multiple DRL coupled ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...

Abstract: Federated learning is a privacy protection method for machine learning, enabling the maintenance of data localization and privacy during training. However, the system heterogeneity leads to ...

Despite the hardships that come with it, this was the approach taken by ArtWorkout founder Aleksandr Ulitin, whose learn how to draw app grew from one modest technical idea. He built a system that ...