💥 The Engineering Digest #6 is here💥

Subscribe

Medium https://medium.com/@yasik

Telegram https://t.me/engdigest

Did I run out of space cats? Absolutely not! So, after a season break the digest is back at its normal cadence 😃

👉👉👉 Extreme Event Forecasting at Uber with Recurrent Neural Networks. At Uber, event forecasting enables us to future-proof our services based on anticipated user demand. The goal is to accurately predict where, when, and how many ride requests Uber will receive at any given time.

https://eng.uber.com/neural-networks/

👉👉👉 Network protocols for anyone who knows a programming language. The network stack does several seemingly-impossible things. …

💥 The Engineering Digest #5 is here💥

Subscribe

Medium https://medium.com/@yasik
Telegram https://t.me/engdigest

This digest isn’t going away, it just took two extra days to collect some awesome stuff to read 😃

👉👉👉 Kappa Architecture. Kappa Architecture is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data store in a Kappa Architecture system is an append-only immutable log

http://milinda.pathirage.org/kappa-architecture.com/

👉👉👉 A huge collection of static analyses tools for pretty much every production programming language. Some of this stuff we are also using at Uber.

https://github.com/mre/awesome-static-analysis

👉👉👉 Storage engine design…

💥 The Engineering Digest #4 is here💥

Subscribe

Medium https://medium.com/@yasik
Telegram https://t.me/engdigest

This week’s digest is short, but very informative :)

👉👉👉 HOODIE: UBER Engineering’s Incremental Processing Framework on Haddop
https://eng.uber.com/hoodie/

👉👉👉 Five Things I’ve Learned As A New Manager At Google. One Googler explains how she’s learned not to (just) be a “crap umbrella” for her team members.
https://www.fastcompany.com/40405205/five-things-ive-learned-as-a-new-manager-at-google

👉👉👉 Meet The Man Who Makes Facebook’s Machines Think. Nearly 3,000 miles away from Facebook’s Menlo Park headquarters, in an old, beige office building in downtown Manhattan, a group of company employees is working on projects that seem better suited…

💥 The Engineering Digest #3 is here💥 — Don’t forget to subscribe in Telegram (https://t.me/engdigest) and now on Medium (https://medium.com/@yasik)

New fact about Jeff Dean — Jeff Dean once shifted a bit so hard it ended up on another computer.

👉👉👉 How To Spot Symptoms Of Employee Burnout On Your Engineering Team. A new survey shows that stress-induced burnout is going to be a big problem for managers in 2017.

https://jell.com/blog/spot-symptoms-employee-burnout-engineering-team/

👉👉👉 Despite its title, a great view on productivity, focus and achieving great results by working smart.

“Figures as different as Charles Dickens, Henri Poincaré, and Ingmar Bergman, working…

💥 Tech digest #2 is here💥 — And now in Telegram as well https://t.me/engdigest

The hero of this digest is Jeff Dean (https://research.google.com/pubs/jeff.html). Jeff Dean is Chuck Norris of computer science. Fact about Jeff Dean: Jeff Dean puts his pants on one leg at a time, but if he had more than two legs, you would see that his approach is actually O(log n). Check out other facts about Jeff, they are hilarious :)

👉👉👉 Q+A With Jeff Dean: The Brain Behind Google’s Artificial Intelligence

https://www.forbes.com/sites/peterhigh/2016/08/01/a-tour-inside-googles-brain

👉👉👉 How Google is remaking itself as a “Machine Learning First” company and the…

I’m starting my new weekly digest that will be primarily focused on 👉 engineers and tech savvy entrepreneurs 👈.

A lot of folks are reaching out to me lately asking about what should they read or study to become better engineers (Type 1 https://teachyourselfcs.com), how to prepare for the interviews in Silicon Valley companies, where to find their next ideas or what challenges to take on next in their career.

I read A LOT and filter out a lot of not worthy readings (it takes a lot of mental energy btw…). So, consider me your personal online bullshit filter :)

…

Meet Keras. Keras is a high-level neural networks library, written in Python.

Since the rise of neural networks in production environments–those with practical real life applications–the field has been primarily a privilege for scientists specializing in machine learning and complex math theories. I like to compare the state of AI by drawing a line back to 50’s, when the same statement applied to early days of computer science. Earlier, to write a program, a scientist had to implement a decent amount of math and then to translate it into machine codes, which ran on a particular hardware.

It was true…