Whether to use End-to-end Deep Learning

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Skills You'll Learn

Data Quality, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Performance Tuning, Keras (Neural Network Library), Debugging, Applied Machine Learning, Machine Learning, Artificial Intelligence

Reviews

4.8 (50,083 ratings)

  • 5 stars
    82.93%
  • 4 stars
    13.62%
  • 3 stars
    2.80%
  • 2 stars
    0.48%
  • 1 star
    0.15%

JB

Jul 1, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

WG

Mar 18, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

From the lesson

ML Strategy

Develop time-saving error analysis procedures to evaluate the most worthwhile options to pursue and gain intuition for how to split your data and when to use multi-task, transfer, and end-to-end deep learning.

Taught By

  • Andrew Ng

    Andrew Ng

    Instructor

  • Younes Bensouda Mourri

    Younes Bensouda Mourri

    Curriculum developer

  • Kian Katanforoosh

    Kian Katanforoosh

    Senior Curriculum Developer

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