Machine Learning Yearning (Andrew Ng)

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Machine Learning Yearning (Andrew Ng)

You will discover how to set up development (dev) sets and test sets in this book, as well as how to agree on ML tactics in a group setting. This article covers how you should set up dev/test sets for contemporary ML projects.

Recommendations for how to set up dev/test sets have been evolving as machine learning moves toward larger datasets.

You will have a thorough understanding of how to define the technical direction for a machine learning project once you have finished reading this book. However, it's possible that your teammates won't comprehend why you're advising a specific course of action. Maybe your team doesn't agree that a single-number evaluation metric should be defined.

How can you convince them? Because of this, I designed the chapters brief so you could print them off and give your teammates just the 1-2 pages they needed to understand. Your team's productivity can be greatly impacted by a few minor modifications in priorities. I hope you can become the superhero of your team by making a couple of these adjustments.

A wide range of industries is being transformed by AI, machine learning, and deep learning. However, developing a machine learning system necessitates making sensible choices:

  • Should you collect more training data?
  • Should you use end-to-end deep learning?
  • How do you deal with your training set not matching your test set?

with a ton more.

In the past, the only way to acquire the skills necessary to make these "strategic" judgments was to serve an extended apprenticeship in a graduate school or business. This book is meant to help you pick up this ability rapidly so that you may develop AI systems more effectively.

Ebook Details

About the Authors
American businessman, computer scientist, investor, and writer Andrew Ng was born in the United Kingdom. He is concentrating on AI and machine learning. [2] Ng is a businessman and investor who co-founded and oversaw Google Brain. He was also a former vice president and chief scientist at Baidu, where he amassed a staff of several thousand people in the company's artificial intelligence division.
Published Date / Year
eBook (Draft, 2018); eBook (MIT Licensed)
MIT License
eBook Format
PDF (118 pages)

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