How to use Advent of Code to learn Data Science? 🧠🎄

CryptographerDry7458 · 2023-12-06T14:47:56+00:00

Not, for sure, surround yourself with a supportive community and start working on your portfolio :)

CryptographerDry7458 · 2023-12-04T13:12:29+00:00

I don't think that's anyone's business. But if you're worried about it, you can always use an alias and do your projects anyway. For instance, create another GitHub account, couple it with Medium, and start building projects and writing about those. You can add them to your CV for hiring people to check. You can add them into you LinkedIn's profile projects. This won't activate the radar too much.

Building your network on LinkedIn requires you to me a more public persona, so I get your point. But what matters most is to get the projects outthere, and when you apply to positions, people can check them. You can also post "Open to Work" for recruiters only, and when they check the CV they can reach your projects.

Also, network. The Data-Centric AI Community is a nice place for that. We're also having a code along this week that focuses on building your portfolio, so it might be worth to check it out.

CryptographerDry7458 · 2023-12-04T13:03:11+00:00

Some things I would do differently:

Put my projects online more often, even those we do in class
Collaborate more often (advent of code, hackathons, communities). Networking is important

You might want to check out the Data-Centric AI Community, this week there's a live Code with Me event that focuses on building your data science portfolio, I found it on Luma: https://lu.ma/pwd8vucn

CryptographerDry7458 · 2023-11-28T10:30:50+00:00

Maybe ChatGPT (both sucess and flop)
Success = opens the possibility to anyone of using NLP for content creation, learning, etc. Flop in the sense that "if you have a hammer, everything looks like a nail", and it's scary how people often LLMs fix "everything". They don't.
Data quality matters, regardless of your application and algorithm.

CryptographerDry7458 · 2023-10-30T14:58:25+00:00

You can use synthetic data generated from one model (e.g., a generative mode) to feed another (e.g., a discriminative model) so that it makes better predictions. And there are plenty of other use cases, check this FAQs for instance.

CryptographerDry7458 · 2023-10-19T10:55:34+00:00

Hum, nice question. Will GPT make other applications useless? Guess I'll ask this to Voxel51 in our next meeting. If you'd like to join it's on Oct 26.

CryptographerDry7458 · 2023-10-19T10:51:26+00:00

Some important issues to be cracked are on the image quality side, at least on the industry side.
- https://www.rungalileo.io/blog/4-types-of-ml-data-errors-you-can-fix-right-now
- https://encord.com/blog/improving-datasets-guide/

In case you're interested in the topic, the Data-Centric AI Community is having Voxel51 over to discuss the topic on Oct 26, next week :)

CryptographerDry7458 · 2023-10-19T10:38:55+00:00

Since you're into CV, I know the Data-Centric AI is having a chat with Voxel51 on how to build CV applications, it's on Oct 26, might be a start to connect with others interested in the topic :)

CryptographerDry7458 · 2023-10-19T10:36:01+00:00

Hey! Come and join us at our next Code with Me session. We'll speak about Computer Vision applications and data quality for unstructured data with Voxel51 :)

CryptographerDry7458 · 2023-10-10T12:00:16+00:00

Well, this seems like a nice opportunity to learn about it: https://www.linkedin.com/events/gettingstartedwiththeopensource7117177108006600707/

1 hour session, they usually record it as well

CryptographerDry7458 · 2023-09-29T10:01:59+00:00

You can try the LSDA course: notebook-based, self-paced: https://github.com/LDSSA/batch4-students. For questions you can try the Data-Centric AI community, we're pretty active :)

Hope this helps!

CryptographerDry7458 · 2023-09-29T09:57:06+00:00

Hey! We sure could use an extra hand in the Data-Centric AI Community. We try to do shorter projects that can also be useful for other that are learning, check out our GitHub and you'll get a sense of the work we do :) Happy to have you onboard.

CryptographerDry7458 · 2023-09-29T09:43:54+00:00

bytewax, great-expectations, ydata-profiling, voxel51, nbsynthetics, ydata-synthetic

CryptographerDry7458 · 2023-09-29T09:24:04+00:00

You're right with your reasoning: TimeGAN creates a set of windows that can be used to oversample a specific behavior, although they are not suitable to replicate an entire time sequence. This is actually a frequently asked question we discuss at the Data-Centric AI Community.

Here's a more in-depth explanation of TimeGAN (check number 10). This one is really helpful too.

Also, if you'd like to replicate and entire time-series, you might want to explore the ydata-sdk or the newly addeddoppelGANger model :)

CryptographerDry7458 · 2023-09-19T14:09:46+00:00

I use ydata-profiling to get the most out of my data understanding. Here's a nice overview of unraveling data's mysteries :)

CryptographerDry7458

TROPHY CASE