1. Weeds out candidates that aren't ready for the job.
2. It significantly cuts down the time we spend talking synchronously.
One problem: It requires extra time from the candidate before the phone interview.
10 machine learning questions you should be able to answer.
I started experimenting with a questionnaire before interviewing candidates. Applicants submit a video or written answers to apply for the position.
Thread: Let's look at 10 of these questions.
1. Weeds out candidates that aren't ready for the job.
2. It significantly cuts down the time we spend talking synchronously.
One problem: It requires extra time from the candidate before the phone interview.
• 249 applicants
• 13 good applications
That's only 5%.
This sucks.
• 44 applicants
• 21 good applications
That's 47%.
This is much better.
Sooner or later, I'll ask these questions, and the candidate will have to answer them.
I'd rather give them space and the opportunity to think about their answers without any pressure.
Those who can't or don't want to answer won't apply. That's fine.
They will fool the questionnaire, not the interview that will come later.
Remember:
• The goal of the questionnaire and the resume is just to decide who moves to an interview.
I want to allow candidates to think creatively and elaborate on their answers.
Preferred: A video response with the answers. Fallback is written answers if the candidate is not comfortable with video.
These cover basic principles that we want to ensure candidates understand.
Every candidate receives the same questions.
Let's go over them:
2. Walk us through the process you follow to select the best machine learning algorithm to solve a problem.
3. Explain the trade-off between bias and variance.
5. How do you handle imbalanced datasets in a classification problem?
6. Explain how you would approach reducing overfitting on a model.
8. What would you expect to see as you vary the batch size when training a neural network?
10. What are the advantages of a Convolutional Neural Network over a fully connected network for image classification?
Follow along for a good bunch of practical tips and epic stories about my experience with machine learning.
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I just finished Eric Adler's The Battle of the Classics, and wanted to say something about Joel Christiansen's review linked below. I am not sure what motivates the review (I speculate a bit below), but it gives a very misleading impression of the book. 1/x
The meat of the criticism is that the history Adler gives is insufficiently critical. Adler describes a few figures who had a great influence on how the modern US university was formed. It's certainly critical: it focuses on the social Darwinism of these figures. 2/x
Other insinuations and suggestions in the review seem wildly off the mark, distorted, or inappropriate-- for example, that the book is clickbaity (it is scholarly) or conservative (hardly) or connected to the events at the Capitol (give me a break). 3/x
The core question: in what sense is classics inherently racist? Classics is old. On Adler's account, it begins in ancient Rome and is revived in the Renaissance. Slavery (Christiansen's primary concern) is also very old. Let's say classics is an education for slaveowners. 4/x
It's worth remembering that literacy itself is elite throughout most of this history. Literacy is, then, also the education of slaveowners. We can honor oral and musical traditions without denying that literacy is, generally, good. 5/x
As someone\u2019s who\u2019s read the book, this review strikes me as tremendously unfair. It mostly faults Adler for not writing the book the reviewer wishes he had! https://t.co/pqpt5Ziivj
— Teresa M. Bejan (@tmbejan) January 12, 2021
The meat of the criticism is that the history Adler gives is insufficiently critical. Adler describes a few figures who had a great influence on how the modern US university was formed. It's certainly critical: it focuses on the social Darwinism of these figures. 2/x
Other insinuations and suggestions in the review seem wildly off the mark, distorted, or inappropriate-- for example, that the book is clickbaity (it is scholarly) or conservative (hardly) or connected to the events at the Capitol (give me a break). 3/x
The core question: in what sense is classics inherently racist? Classics is old. On Adler's account, it begins in ancient Rome and is revived in the Renaissance. Slavery (Christiansen's primary concern) is also very old. Let's say classics is an education for slaveowners. 4/x
It's worth remembering that literacy itself is elite throughout most of this history. Literacy is, then, also the education of slaveowners. We can honor oral and musical traditions without denying that literacy is, generally, good. 5/x
