วีดีโอ

Congratulation 🎉🎉keep going

Great idea

does neptune track code changes?

Bravo ingénieur! Proud of you.

Félicitations mon frère !!

Bravo mon ingénieur Tu fais ma fierté Va de l'avant 👌

Great young boy! so proud of you👏

Excellent Jonas! I’m so proud of you 👏🏽👏🏽👏🏽

Thank for sharing 👍

Papergen templates are soooo good for every assignment i have

Nice interview

very interesting podcast, thank you!

About time

You are stunning and your mindset is very great , best wishes .

Keep them coming 🫡

Tks🎉

That's the answer you get in an elevator if you tell a good PhD student to give you 'the elevator pitch'

Славянка

.😊

Can you guys explain the difference between Fireworks and Groq?

so basically you patch the unix time function to html and JS... that's really cute.

20% in...now over...and i dont know what embeddings or sphere you are rambling about

Still don’t know 😆

An year ago people said it creates opportunities (Felt really dumb listening it). Now claiming it is removing their jobs.

Randomly saw the ad on TH-cam. Neat software for potential commercial ai development.

Interesting series. Looking forward to more.

Honestly I disagree entirely. These "data sets" are almost entirely user-generated content, "owners" are almost entirely giant tech companies. This entire narrative is about monetizing their investment in hoarding data, rather than protecting the intellectual output of individuals. This thinking mainly benefits big companies when LLMs should benefit humanity. We're at a fork in the road and opting to hand the keys to the kingdom only to the biggest corporations colluding with one another.

And how do you implement verification checks?

i really appreciate your videos, the way you instruct us, its very helpful with inspiration to be a great trader.i think one of the best strategy I found on youtube. Thanks for making such videos for us.

very good, but Federico mic quality make it really hard to understand him

1:07 my ennemy 😂

Can we evaluate LLM models like open ai, Claude or any other LLM model for specific tasks using neptune?

Shhh. Let them fall behind so that the people that see it can rise to the occasion lol

I dont see foundational models replacing Deep Learning Engineers (often carrying a title of "Data Scientist") anytime soon. The foundational models wont replace every single use case of Deep Learning or ML where training models still needed. Using LLM is often an overkill where BERT would suffice or using GPT4-v for Object Detection / Segmentation tasks. To be cost-effective, models still need to be fine-tuned, data cleaned and selected, etc. An ML Engineer won't be able to do it as good as a Deep Learning Eng.

Comment prendre en directs

Freedom for innocent Kabyles unjustly

The interesting part is that when we go from classic coding to ML and now to LLMs, the main characteristic is the increase of the ability to deal with real world, organic situations. This is a puts a tremendous pressure on control and test sides because they want well defined and controlled boundaries on the system. So the power and flexibility of ML an LLM are also they curse when it comes to OPS. As LLMs interact using natural language, it is almost as if we would have to put the team inside the version control system. Maybe we should think in LLM models as members of the team: we don't version people, we train and certificate them. Another way of thinking would be to do pair programming with the models: one LLM develops, other creates test cases, both in a competition

Are these tools enough for mlops GitHub , maven, Jenkins, docker, kubernetes, but I want to automate 1. EDA or visualisation 2. Data preprocessing 3. Website development in ML

If you think Classic NLP is dead then you do not know how these models work at all...

robots will replace manual labor trade school lvl and ai will replace higher learning jobs collage master lvl

Great podcast and nice to hear someone talking highly about bootcamps. A data science bootcamp changed my life, super lucky to have done it.

ऐ😊😊😊😊😊😊😅 1:06 1:06

Do you have the notebook online somewhere?

Full ML Platform podcast episode: th-cam.com/video/G5dzU4Ye4nU/w-d-xo.html

Full ML Platform podcast episode: th-cam.com/video/G5dzU4Ye4nU/w-d-xo.html

Full ML Platform podcast episode: th-cam.com/video/G5dzU4Ye4nU/w-d-xo.html

Disappointing

To be honest, to say that LLMs solve problems better than NLP shows me that you didn’t dig into the subject deeply enough. They can and should be combined very well plus there’s the question of costs. Some tasks are done much better by classical NLP models. For instance, try to run entity extraction using an LLM on a huge data corpus. Good luck with that :)

Funny how we (data/ML people) build things that will potentially stole our own job. We are working on our way to the precipice!!