Why human-level performance? - Structuring Machine Learning Projects

Описание: Link to this course:
https://click.linksynergy.com/deeplin...
Why human-level performance? - Structuring Machine Learning Projects
Deep Learning Specialization
You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how.

Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two flight simulators that let you practice decision-making as a machine learning project leader. This provides industry experience that you might otherwise get only after years of ML work experience.

After 2 weeks, you will:
Understand how to diagnose errors in a machine learning system, and
Be able to prioritize the most promising directions for reducing error
Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance
Know how to apply end-to-end learning, transfer learning, and multi-task learning

I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time.

This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization.
Machine Learning, Deep Learning, Inductive Transfer, Multi-Task Learning
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!).,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.

Why human-level performance? - Structuring Machine Learning Projects
Copyright Disclaimer under Section 107 of the copyright act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.