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  2. fast.ai - Wikipedia

    en.wikipedia.org/wiki/Fast.ai

    The free MOOC "Practical Deep Learning for Coders" is available as recorded videos, initially taught by Howard and Thomas at the University of San Francisco. In contrast to other online learning platforms such as Coursera or Udemy, a certificate is not granted to those successfully finishing the course online. Only the students following the in ...

  3. 10 Free Online Certification Courses to Advance Your Career - AOL

    www.aol.com/news/10-free-online-certification...

    Certificate programs can lead to high-paying jobs -- so if you don't have to pay for a certification, it's a real opportunity. 10 Free Online Certification Courses to Advance Your Career Skip to ...

  4. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    Since 2017, Ng has been advocating the shift to high-performance computing (HPC) for scaling up deep learning and accelerating progress in the field. [citation needed] In 2012, along with Stanford computer scientist Daphne Koller he cofounded and was CEO of Coursera, a website that offers free online courses to everyone.

  5. Jeremy Howard (entrepreneur) - Wikipedia

    en.wikipedia.org/wiki/Jeremy_Howard_(entrepreneur)

    Jeremy Howard (born 13 November 1973) is an Australian data scientist, entrepreneur, and educator. [1]He is the co-founder of fast.ai, where he teaches introductory courses, [2] develops software, and conducts research in the area of deep learning.

  6. Deeplearning4j - Wikipedia

    en.wikipedia.org/wiki/Deeplearning4j

    Deeplearning4j serves machine-learning models for inference in production using the free developer edition of SKIL, the Skymind Intelligence Layer. [27] [28] A model server serves the parametric machine-learning models that makes decisions about data. It is used for the inference stage of a machine-learning workflow, after data pipelines and ...

  7. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

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