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  1. en.wikipedia.org › wiki › Andrew_NgAndrew Ng - Wikipedia

    Andrew Yan-Tak Ng (Chinese: 吳恩達; born 1976) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). [2]

  2. www.andrewng.orgAndrew Ng

    Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.

  3. DeepLearning.AI | Andrew Ng | Join over 7 million people learning how to use and build AI through our online courses. Earn certifications, level up your skills, and stay ahead of the industry.

  4. Andrew Ng’s Machine Learning Collection. Courses and specializations from leading organizations and universities, curated by Andrew Ng. Andrew Ng is founder of DeepLearning.AI, general partner at AI Fund, chairman and cofounder of Coursera, and an adjunct professor at Stanford University.

  5. View Andrew Ngs profile on LinkedIn, a professional community of 1 billion members.

    • DeepLearning.AI
  6. In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more.

  7. Articles 1–20. ‪Stanford University‬ - ‪‪Cited by 260,382‬‬ - ‪Machine Learning‬ - ‪Deep Learning‬ - ‪AI‬.

  8. Andrew Ng is Founder of DeepLearning.AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University.

  9. Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (gen...

  10. Director, Stanford Artificial Intelligence Lab Associate Professor Computer Science Department Stanford University. Research interests: Artificial Intelligence, Machine learning, Unsupervised feature learning and Deep learning, Neuroscience-informed AI.

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