Structuring Machine Learning Projects

This course is part of Deep Learning Specialization

Instructors: Andrew Ng +2 more

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Skills you'll gain

  •   Tensorflow
  •   Deep Learning
  •   Keras (Neural Network Library)
  •   PyTorch (Machine Learning Library)
  •   Machine Learning
  •   Debugging
  •   Applied Machine Learning
  •   Data Quality
  •   Artificial Intelligence
  •   Performance Tuning
  • There are 2 modules in this course

    By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.

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