dude why does this assume that I would be running it on a linux based machine???

bro great video, i really enjoi it, thank u, but bro, at 1:40 my heart told me bye, why it so scary there uh

Amazing guys!!

So how would you suggest we follow this video or the course. Should we just clone the repo and keep running the code? Should we create a new repo and start adding all the files from scratch? I am confused and lost, please help!

Great format. You have. Niche here. The 6 minute format is perfect for consuming and gives enough detail for me to know enough and follow up myself

Hi, Please monetise your channel, I turned off the adblockers just to view your video, thanks. Do you have any course on Spark, Flume, Beam? Please do let me know.

This video is good no question about it and thank you for this awesome video but I humble request to the author of this video that please do not do the transition video sound like 1:22. IDK but it hurts my ears.

Boss 💪🏾

Thank you for inspiring. I have zero experience and knowledge in coding. What is your advice in where to start?

Practical FYI: One of the largest challenges is to actually get meaningful data streams from products and the often naively written CRUD products by full stack engineers. There is an open source project called “Debezium” that allows to create change and event data from database changes. For the other way around, where a complex Kafka stream system already exists, there is a project called “Materialize” which makes feature engineering (combining many streams) much easier than writing it imperatively in code. For finding interesting relationships in event streams, there is also a project called “Memgraph”. Maybe this info helps for the most common challenge to actually get to meaningful data ❤️ subscribed

Good video but it would be great if you could type the code and explain what the code is actually doing, instead of just showing snippets. I would hate to watch a longer more elaborate 20 min video. Hoping for more content like this this

Please please please make an end to end project video or course to explain in practical. You are great in explaining. If you will not, please recommend resources or courses to learn MLOps

Can you do one complete project for MLOps ( development and deployment) ?

yaa, really helpful content about production for beginners , thanks a lot

Great explanation, But would be alot better & helpful for beginners if u show a working demo as well.

thanks..but you should have shown the process practically, good info though

please add all videos about ML production in one playlist, thanks for awesome real world content

This is great.. but I wonder why ppl still insist on using docker. These folks changed their business model years ago. Even the free model has limits: 200 image pulls per 6 hours. Now as far as poetry is concerned I use it everyday!

learned a lot from your videos Pau. Do you have a starter course I could take in order to learn MLOPS and deploying machine learning models into production? I already know how to train an ML model, and deploying it to production is quite a headache for me. Thanks :D

Why not Google Colab?

Thanks Pau and Paul, great tutorials! May I ask why we're using this setting "PYTHON_KEYRING_BACKEND=keyring.backends.null.Keyring"?

Suggestion: a video on how to read the metrics and understand the model behavior, and how to fix it by going back to your data And how you really decide which model should go to production, Before you really go to production!

Very precious video, 3 years of experience in less than 10 minutes! I hope juniors find this gem.

Hi, thanks for pathway btw can we modify pathway with google AI API key

Time series data was not generated in the previous video, only the problem was framed. Am I missing something?

nice job! my KTH

'PromoSM'

Thanks for your videos! Great stuff. I'm looking forward to more.

could you please provide the link to the dataset, I will be grateful

Very good information. Thank you bro!

I love you content man, keep it up! Really concise and living up to the name of Real world ML🎉 Hoping to have and watch your end-to-end project tutorial playlist

Your explanation is clear and useful, keep making this great content please!

Really appreciate the content you're putting out on MLops...it's so rich thanks a lot...i am big fan

Awesome

Thank you for your videos! Waiting for more. Good luck on your journey.

Excellent. Thanks so much! Greetings from Brazil.

If I were you, after seeing my lookalike, I could've said "I've never seen this man in my life"😊

This is great. Would you mind in explaining the full tutorial so that it will be easy for the learners/beginners to understand the context.

Amazing video brother!

Hey, thanks for the idea. I want to implement this but am a bit concerned about the sentiment extraction step. Could this just be assigning a 1-10 value representing how positive/negative each news data point is? What kind of LLM setup can I use to do this very cheaply?

is there another way to deploy docker images other than quix cloud?

Great video, thanks! Quick question: why would you want containerize this streamlit app? Streamlit already supports free hosting for example over github. Whats the benefit of docker here? Second question: is there a free docker container hosting service? So i can share it with others and run it somewhere else?

But how can we deploy that docker image, and assure it runs live,how can we add CI/CD to it as well?

Hi. You don't seem like native English speaker. What is your native??

you look like jesus of IT community

Thanks for sharing Pau.

Thank you! Your website from description is cool as well.

Dude amazing content! have you tried the new uv python packaging that uses rust? Wishing you the best!

Wondering, do you have any video on that where you have applied all of these 3 tips with end to end small project? If you've, can you please share the links with us. Btw, you're contents are always awesome! Thanks a million.

Amazing tips !! Thank you!