When.com Web Search

  1. Ads

    related to: andrew ng deep learning slides

Search results

  1. Results From The WOW.Com Content Network
  2. Google Brain - Wikipedia

    en.wikipedia.org/wiki/Google_Brain

    Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the newer umbrella of Google AI, a research division at Google dedicated to artificial intelligence.

  3. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    Andrew Yan-Tak Ng (Chinese: 吳恩達; born April 18, 1976 [2]) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). [3] Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu , building the company's Artificial Intelligence Group ...

  4. Nvidia GTC - Wikipedia

    en.wikipedia.org/wiki/Nvidia_GTC

    Andrew Ng, Founder and CEO, DeepLearning.AI, Landing AI: The Data-centric AI Movement; Lina Halper, Principal Animation Engineer, Nvidia: Deep Dive: One Click Animation Retargeting in Omniverse; Douwe Kiela, Head of Research, Hugging Face: BigScience: Building a Large Hadron Collider for AI and NLP

  5. Quoc V. Le - Wikipedia

    en.wikipedia.org/wiki/Quoc_V._Le

    In 2011, Le became a founding member of Google Brain along with his then advisor Andrew Ng, Google Fellow Jeff Dean, and researcher Greg Corrado. [5] He led Google Brain ’s first major breakthrough: a deep learning algorithm trained on 16,000 CPU cores , which learned to recognize cats by watching YouTube videos—without being explicitly ...

  6. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    The design has its origins from pre-training contextual representations, including semi-supervised sequence learning, [24] generative pre-training, ELMo, [25] and ULMFit. [26] Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus .

  7. Transfer learning - Wikipedia

    en.wikipedia.org/wiki/Transfer_learning

    Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.