babo

That would make it even worse.

A car could be self-driven while not connecting to any external networks. It still can get fresh traffic or weather data, but with those, you can't take over a car to make it a weapon.

Using more than one sensor helps, radar could see a black car, while lidar not.

That's something what's easy to train. Each of these are a bit country specific like how a road sign is mounted and where, but this is far from a real problem.

There are limits for sure, but actually it's quite possible to write bash code at scale, but it requires some discipline and practice. It's hard to avoid it.

It would be interesting to see it as an editing mode in atom.io or vs code!

Listen to them. As a consultant this is the key, understand the customer first to provide them unique, tailed answers.

As a Python 2.7 project why would I trust more to this unofficial version with a lot of backported code compared to the tried and tested 2.7 to 3 route?

What would happen with my python 2.8 when it needs to be converted to the official python 3?

The purpose of these puzzles is to move you out of your comfort zone. Take the none familiar indentation as part of that experience.

CDN providers has a highly volatile infrastructure setup, short TTL helps them to dynamically reallocate resources. Just as an example, cache invalidation could be implemented with a switch of DNS records.

Not so for CDN content.

This technique could help to break this monopoly of big data as it relies less on labelling which is even harder and more expensive for a large dataset than the actual data.

10 hours per week

With self driving cars you need to address very different topics to make it happen. From the nanodegree program I'm expecting a comprehensive curriculum which touches the required theoretical background but pragmatic. Looking forward to start it at November.

In the long run my goal is to switch to this area, either as an employee or building a startup.

There are three cohorts at the beginning, 500 starts in October, 1500 in November, and 2500 in December. I'm at the November batch like you, paid the fee already.

Recently I built a similar machine with a single GTX 1080 for $2500 in Norway.

Autoscaling as not necessary driven by CPU load.

For me that was the great part of the post mortem, they identified the response process itself as the root cause.

Apparently a lot of parts of the system were on alarm.

How do you compare the geo-replication capabilities of Kafka vs. Pulsar?

Just a note, even Cloudformation is not covering all AWS features. It's more complete but not 100%.

Works fine after adding a minimal config {"magicpython": "Python 3"} at the Kernel Mappings setting and setting PYTHONPATH at the command line when running atom. It's kinda cool to manage your kernels from the editor!

Take that temporary EC2 instance as a container just there for that half an hour to get the job done, they fix software installation, access rights etc. on behalf of you.

Is that code answers your question? No offense but the main message of that talk is if you can do a for loop than you can do statistics simulation in any programming environment. Like in R.

m <- 0 nexp <- 100000

for (i in 1:nexp) { if (sum(rnorm(30, mean=0, sd=1) < 0) >= 22) { m <- m + 1 } }

print(m / nexp)

I found this comment on youtube by asperous helpful: If you are on a mac you can go under accessibility -> sound -> play stereo as mono. This will balance the sound.

Is python matters here?

- algo-005

- nlp

- machlearning-001

- maththink-004

- mmds-002

- pgm-003

- gametheory-003

- compilers-003

Actually it's a beta version, it would be great to correct the misleading title.

Sure, but that's the deal. I'll buy the latest nVidia 1080 card as soon as I can but renting these custom chips per minute would be a way better option for me.

SGI Workstations like Indigo2 or Indy. They were heavy and noisy beasts but for me it was a flawless experience to work with.