Hacker News Books

40,000 HackerNews book recommendations identified using NLP and deep learning

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The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations

Gene Kim , Patrick Debois , et al.

4.6 on Amazon

2 HN comments

Deep Learning with Python

François Chollet

4.5 on Amazon

2 HN comments

Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition

Stefan Jansen

4.5 on Amazon

2 HN comments

Building Microservices: Designing Fine-Grained Systems

Sam Newman

4.5 on Amazon

2 HN comments

Team Topologies: Organizing Business and Technology Teams for Fast Flow

Matthew Skelton , Manuel Pais , et al.

4.6 on Amazon

2 HN comments

UNIX and Linux System Administration Handbook

Evi Nemeth, Garth Snyder, et al.

4.7 on Amazon

2 HN comments

Building Mobile Apps at Scale: 39 Engineering Challenges

Gergely Orosz

5 on Amazon

2 HN comments

Release It!: Design and Deploy Production-Ready Software

Michael T. Nygard

4.7 on Amazon

2 HN comments

Advances in Financial Machine Learning

Marcos Lopez de Prado

4.5 on Amazon

2 HN comments

How Google Works

Eric Schmidt and Jonathan Rosenberg

4.5 on Amazon

2 HN comments

Start with Why: How Great Leaders Inspire Everyone to Take Action

Simon Sinek

4.6 on Amazon

1 HN comments

Press Reset: Ruin and Recovery in the Video Game Industry

Jason Schreier

4.4 on Amazon

1 HN comments

The Elder Scrolls: The Official Cookbook

Chelsea Monroe-Cassel

4.9 on Amazon

1 HN comments

Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People

Aditya Bhargava

4.6 on Amazon

1 HN comments

The Phoenix Project (A Novel About IT, DevOps, and Helping Your Business Win)

Gene Kim

4.7 on Amazon

1 HN comments

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bwh2onJune 16, 2021

I enjoyed these books:

* Strategy Rules

* How Google Works

* Founders at Work

throwaway29303onMay 21, 2021

No, however, please note the following:

Companies, like customers, have requirements for their needs. If a company needs a potential employee to know how to invert a binary tree then it's in their right to find one.

In Google's case, as you're probably alluding to[0], although I might be mistaken, they've always had the reputation for seeking the best qualified people[1] for their work. I mean look at who's working for them - there's a lot of well-known people in their respective fields that are working for them.

Moreover, I think that the point of these tests is to help assess a potential employee's abstract thinking. And, probably, to understand one's thought process behind the solution - if there's one - to the given problem. (Which, by the way, might be helpful if you're trying to solve AI - something that's right up in Google's alley ;).

Despite the backlash over this, I believe companies will keep doing these types of tests for a long, long time. I don't think this is going away that easily. And I also think that, in the future, these tests might be done in a way you won't even know you're being tested for.

[0] - https://twitter.com/mxcl/status/608682016205344768

[1] - I understand that "best qualified" here might mean different things for different people, but you should take it literally, that is, people who are above the average in terms of abstract thinking. I suggest you read How Google Works[2], they've coined the term Smart Creative which is kind of(?) related to this.

[2] - https://www.howgoogleworks.net/

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