Structuring Machine Learning Projects
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Structuring Machine Learning Projects

Highlights

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. 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.

About the Course Provider

Coursera provides access to more than 3000+ courses across a wide variety of subjects in parntership with different universities and organizations.

Course by

  • self
    Self paced
  • dueration
    Duration 7 hours
  • domain
    Domain Data Science & AI
  • subs
    Monthly Subscription
    Course is included in
    1. Starter @ AED 99 + VAT
    2. Professional @ AED 149 + VAT
  • fee
    Buy Now AED 170.99 + VAT
  • language
    Language English