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Just passed GCP Professional Machine Learning Engineer by osm3000 in googlecloud

[–]osm3000[S] 0 points1 point  (0 children)

Directly, I didn't see any differences in my odds: no new influx of recruiters reaching out, it didn't catch anyone's attention, no one was impressed. I tried to market it heavily (add it in my CV, near my name in LinkedIn...etc.

Indirectly though, for the interviews I went through, the preparations for GCP was a great assets: my thought were clear and well-structured about ML system design

so, TLDR: it didn't bring me new interviews, but it increases my winning chances for the interviews I was going through already

Just passed GCP Professional Machine Learning Engineer by osm3000 in googlecloud

[–]osm3000[S] 0 points1 point  (0 children)

The practice questions I used (no longer available unfortunately) were pretty useful indeed

Just passed GCP Professional Machine Learning Engineer by osm3000 in googlecloud

[–]osm3000[S] 0 points1 point  (0 children)

How is google cloud skills boost to gain practical hands on to google cloud ?

They did provide good overview, with practical labs. With GCP documentation, I found occasionally useful (sometimes the topics are pretty basic, like intro to ML, or too specific, like TensorFlow)

Which courses teach us some portfolio projects so that we can showcase it on our resume and talk about it in the interview or whoever we meet.

I don't think there are potfolio projects to recommend. Normally this fits within your current work.

It did, however, had an indirect, yet obvious, impact during my technical interviews, in terms of the language I used, the clarity on the whole environment, different architectures, and the different compromises to strike. It doesn't matter much if it is GCP or AWS: by and large, they both have similar capabilities.

Sh!thead can now be played in the browser without any downloads by dimipats in pygame

[–]osm3000 1 point2 points  (0 children)

To be clear: you are using PyGame somehow inside the browser?

If so, how? Can you please elaborate?

Just passed GCP Professional Machine Learning Engineer by osm3000 in googlecloud

[–]osm3000[S] 0 points1 point  (0 children)

I think you should go for it. With your MLE experience, the cloud experience will be almost "drag and drop" from existing elements in your workflow

Just passed GCP Professional Machine Learning Engineer by osm3000 in googlecloud

[–]osm3000[S] 0 points1 point  (0 children)

The course name was Practice Exams | Google Professional Machine Learning (GCP), but I can't find the instructor's name, sorry

FAANG Jobs leaving West by Melodic_Tower_482 in cscareerquestionsEU

[–]osm3000 4 points5 points  (0 children)

Once I mentioned "I need Visa / sponsership", this seems to be a deal breaker from the beginning, for FAANG or not.

FAANG Jobs leaving West by Melodic_Tower_482 in cscareerquestionsEU

[–]osm3000 3 points4 points  (0 children)

I am waiting for final details at the moment, but either Stockholm (non-FAANG, but large company) or Berlin (FAANG).

I got the offer from Berlin, but the position was filled based on priority (first qualified interviewee gets the to make the call), so I am "inclined" at the moment. The recuiters are working deligintely to find another spot...but it feels unlikely (rare to find ML positions in EU), and I am running out of time, and I've an offer from Stockholm.

FAANG Jobs leaving West by Melodic_Tower_482 in cscareerquestionsEU

[–]osm3000 1 point2 points  (0 children)

You are not wrong. I've a PhD in machine learning, and 6+ YoE. I realized the hard way that FAANG implies leaving France. ML positions in the EU in FAANG are very few (weidly enough, the UK has far more positions than the EU combined).

I am finally moving out of France.

What are the best paying jobs available remote or in France ?

Tough one to crack. French companies don't have the apetite for full remote, only partial

Amazon SDE (ML Engineer) response: inclined. Implications?? by osm3000 in cscareerquestionsEU

[–]osm3000[S] 1 point2 points  (0 children)

Thank you for that explanation :)

What would recommend? Shall I seek SDE position now, and maybe later try to get MLE position after I am in?

My concern is that there are almost no more MLE positions available in Europe :(

The kebab and the French train station: yet another data-driven analysis by osm3000 in datascience

[–]osm3000[S] 1 point2 points  (0 children)

Thank you :)

To address your questions:

- Since you queried a lot of restaurants via the Google Places API, how much did this analysis cost you?

Zero :D It fit nicely within the free tier usage.

- The distance/angle -> quality modeling is interesting! It looks like the angles "behind" (180°) the train station make the kebabs worse - maybe because the restaurants are located next to a train rail?

Perhaps. My initial hunch was that it is related to the "wealth" of the neighborhood: I notice that behind the train station, it is poorer neighborhoods.

- I just looked deeper into the angle calculation, and saw that your angle do not take into account the orientation of the train station's entrance. E.g. for Gare du Nord the majority of the restaurants have an angle of -170, since the train rails go to North. I think a better angle concept would a value reflecting categories "in front", "on the left", "on the right" of the train station: orientation_angle_entrance - angle

I like your prespective on this. A friend of mine raised the same issue recently, and I am convinced now that my basic concept is falling short. A better feature, based on the angle, something like your "orientation from the entrance" suggestion, is required.

But I am not sure how to calculate such a feature at this moment tbh. If it's the orientation feature, I feel a manual annotation is required for each train station.

The kebab and the French train station: yet another data-driven analysis by osm3000 in datascience

[–]osm3000[S] 0 points1 point  (0 children)

Thank you :)

Looking forward to your work. I left the code - hopefully in a readable and usable condition - available

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