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Everyday ML Questions - Vol 1 • Apr 2022

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Everyday ML Questions - Vol 1 • Apr 2022

$9.99
bnomial
19 ratings

A different way to learn

This book aims to teach you something new, one question at a time.

There are 20,000 + 1 machine learning and data science books out there. That's great, but we wanted something different.

In April, we started publishing one machine learning question every day. A quick story with a problem and a few possible answers. Something quick, practical, and fun that you could solve in a few seconds. In just 30 days the site attracted more than 80,000 visitors and every day over 1,500 people answer the question and it keeps growing.

Many reached out asking for previous questions.

This book is a compendium of the 30 questions we published online from April 1 to April 30, 2022.

Are you interested in more than this book? Check out here!

The structure

The book is structured in two main sections: questions come first, followed by the answers and explanations.

Every question tells you a quick story and gives you four possible answers. We try to dive as deep as possible with the explanations, to give you as many details as you need to understand the correct answer.

Here is the list of the 30 questions covered in the book:

  1. Hot dog or not hot dog
  2. Daniella is looking at ReLU
  3. A few regression models to start
  4. Odd one out
  5. Eliana knew the answer immediately
  6. The ideas behind Deep Learning aren’t new
  7. Histogram head and tails
  8. We need more capacity
  9. Helping Madeline remember
  10. Peter needs a better balance
  11. I’m frustrated with my training loss
  12. Ted wants to sell more cars
  13. Handling missing values
  14. The mysterious case of the strange loss
  15. Looking behind François’s Tweet
  16. Patricia is building a logistic classifier
  17. The birthday paradox
  18. Keeping pedestrians safe
  19. Thinking about softmax
  20. Alice can’t remember how One-Hot Encoding works
  21. The anatomy of ReLU
  22. Australian birds
  23. Breaking a function down into pieces
  24. Mia and the feedback loop
  25. Harper is dealing with small gradients
  26. Exploring data before anything else
  27. Susan needs to make a decision
  28. Linear regression by hand
  29. 20,000 sunny and cloudy samples
  30. The true meaning of hyperparameter tuning

Is this book for you?

Interest in artificial intelligence is at an all-time high. Whether you are a programmer or a student interested in data science and machine learning, this book is definitely for you. We cover a wide array of concepts to help you practice and build a much more substantial career in the industry.

30-day money-back guarantee

If you read this book and you didn't learn anything, we'll send you a refund.

Final word

Every day we publish a new question. You can go to bnomial.com and answer them right when they go live!

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Download "everyday ml questions" e-book in PDF and ePUB format.

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