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2. Multiple instance learning - Wikipedia

   en.wikipedia.org/wiki/Multiple_Instance_Learning

   Depending on the type and variation in training data, machine learning can be roughly categorized into three frameworks: supervised learning, unsupervised learning, and reinforcement learning. Multiple instance learning (MIL) falls under the supervised learning framework, where every training instance has a label, either discrete or real valued ...

3. Deep learning - Wikipedia

   en.wikipedia.org/wiki/Deep_learning

   In the late 2000s, deep learning started to outperform other methods in machine learning competitions. In 2009, a long short-term memory trained by connectionist temporal classification ( Alex Graves , Santiago Fernández, Faustino Gomez, and Jürgen Schmidhuber , 2006) [91] was the first RNN to win pattern recognition contests, winning three ...

4. Attention (machine learning) - Wikipedia

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

   The machine learning-based attention method simulates how human attention works by assigning varying levels of importance to different words in a sentence. It assigns importance to each word by calculating "soft" weights for the word's numerical representation, known as its embedding, within a specific section of the sentence called the context window to determine its importance.

5. Machine learning in physics - Wikipedia

   en.wikipedia.org/wiki/Machine_learning_in_physics

   Classical machine learning is effective at processing large amounts of experimental or calculated data in order to characterize an unknown quantum system, making its application useful in contexts including quantum information theory, quantum technologies development, and computational materials design.

6. Machine learning in earth sciences - Wikipedia

   en.wikipedia.org/wiki/Machine_learning_in_earth...

   Applications of machine learning in earth sciences include geological mapping, gas leakage detection and geological features identification.Machine learning (ML) is a type of artificial intelligence (AI) that enables computer systems to classify, cluster, identify and analyze vast and complex sets of data while eliminating the need for explicit instructions and programming.

7. Feature (machine learning) - Wikipedia

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

   In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis. When representing images, the feature values ...