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2. Timeline of machine learning - Wikipedia

   en.wikipedia.org/wiki/Timeline_of_machine_learning

   1950s. Pioneering machine learning research is conducted using simple algorithms. 1960s. Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s. ' AI winter ' caused by pessimism about machine learning effectiveness. 1980s.

3. Extreme learning machine - Wikipedia

   en.wikipedia.org/wiki/Extreme_learning_machine

   e. Extreme learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with a single layer or multiple layers of hidden nodes, where the parameters of hidden nodes (not just the weights connecting inputs to hidden nodes) need to be tuned.

4. ChatGPT - Wikipedia

   en.wikipedia.org/wiki/ChatGPT

   ChatGPT is a chatbot developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

5. Outline of machine learning - Wikipedia

   en.wikipedia.org/wiki/Outline_of_machine_learning

   The following outline is provided as an overview of and topical guide to machine learning: Machine learning – subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. [1] In 1959, Arthur Samuel defined machine learning as a "field of ...

6. Active learning (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Active_learning_(machine...

   e. Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

7. Boosting (machine learning) - Wikipedia

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

   Machine learningand data mining. In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, variance. [1] It is used in supervised learning and a family of machine learning algorithms that convert weak learners to strong ones. [2]