Reinforcement Learning: Fundamentals and Applications in AI
Reinforcement Learning (RL) has emerged as a pivotal branch within artificial intelligence (AI), drawing inspiration from the behaviorist principles of...
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Active Learning: How to Reduce the Need for Labeled Data
Active learning in artificial intelligence has emerged as a response to a fundamental problem in supervised learning: the need for...
Machine Learning in the Energy Field: Prediction and Optimization
The effective harnessing of energy sources, both renewable and non-renewable, is one of the most imperative challenges humanity faces. Advances...
Unsupervised Learning: Methods and Techniques
Unsupervised learning is a fundamental branch of Artificial Intelligence, where models are trained using unlabeled or unclassified data. Unlike supervised...
Data Preprocessing Techniques in Machine Learning
Data preprocessing is a crucial pillar in building robust and efficient Machine Learning (ML) models. As we move towards a...
