From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...
Abstract: In response to the escalating threat of fake news on social media, this systematic literature review analyzes the recent advancements in machine learning and deep learning approaches for ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Abstract: This research examines the utilization of machine learning to proactively forecast cybersecurity problems, hence reducing the likelihood of substantial system interruptions. Utilizing the ...
Adaptive systems were supposed to simplify decision-making. Instead of hard-coded rules, engineers built models that could learn from data, respond to change, and improve over time. That promise still ...
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