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2. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

3. Feature engineering - Wikipedia

   en.wikipedia.org/wiki/Feature_engineering

   Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...

4. Feature (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Feature_(machine_learning)

   In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.

5. Feature learning - Wikipedia

   en.wikipedia.org/wiki/Feature_learning

   Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare transfer learning). [1] In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed ...

6. Transformer (deep learning architecture) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(deep_learning...

   Transformers were first developed as an improvement over previous architectures for machine translation, [4] [5] but have found many applications since. They are used in large-scale natural language processing, computer vision (vision transformers), reinforcement learning, [6] [7] audio, [8] multimodal learning, robotics, [9] and even playing ...

7. Rule-based machine learning - Wikipedia

   en.wikipedia.org/wiki/Rule-based_machine_learning

   Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. [ 1 ] [ 2 ] [ 3 ] The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that ...