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  2. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [ 23 ] [ 24 ] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6).

  3. A self-taught engineer at Google shares the 8 best Google ...

    www.aol.com/self-taught-engineer-google-shares...

    Gaba is a self-taught engineer who used Google's free and auditable courses when learning to code. Gaba says there's a course for programmers at every level on topics like Python and generative AI.

  4. Google Brain - Wikipedia

    en.wikipedia.org/wiki/Google_Brain

    The Google Brain team contributed to the Google Translate project by employing a new deep learning system that combines artificial neural networks with vast databases of multilingual texts. [21] In September 2016, Google Neural Machine Translation (GNMT) was launched, an end-to-end learning framework, able to learn from a large number of ...

  5. Google Digital Garage - Wikipedia

    en.wikipedia.org/wiki/Google_Digital_Garage

    Google Digital Garage is a nonprofit program designed to help people improve their digital skills. [1] It offers free training, courses and certifications [ 2 ] [ 3 ] via an online learning platform .

  6. Coursera - Wikipedia

    en.wikipedia.org/wiki/Coursera

    A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of completion. [57] [60] Other Coursera courses, projects, specializations, etc. cannot be audited—they are only available in paid versions.

  7. Google JAX - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

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