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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. Recently, artificial neural networks have been able to surpass many previous approaches in performance.

3. Synthetic data to train machine learning models may be key in ...

   www.aol.com/finance/synthetic-data-train-machine...

   Synthetic data is taking off. By this year, 60% of the data used to train Al models will be synthetic, Gartner has predicted. That’s a huge jump from just 1% in 2021. With help from generative ...

4. 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.

5. Tom M. Mitchell - Wikipedia

   en.wikipedia.org/wiki/Tom_M._Mitchell

   Tom Michael Mitchell (born August 9, 1951) is an American computer scientist and the Founders University Professor at Carnegie Mellon University (CMU). He is a founder and former Chair of the Machine Learning Department at CMU. [4] Mitchell is known for his contributions to the advancement of machine learning, artificial intelligence, and ...

6. The AI trade has a Jamie Dimon problem: Morning Brief - AOL

   www.aol.com/finance/ai-trade-jamie-dimon-problem...

   But Marc Benioff used this framing back in 2017 — the same year Dimon himself first referenced AI. "Since the firm first started using AI over a decade ago, and its first mention in my 2017 ...

7. 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 ...