ML Explained

I like to make memes and sometimes write about ML concepts

[ML Explained @mlexplained]

First Brilliant move after I don't know how long !

[ML Explained @mlexplained]

Answer this
🐷 - 🥧 = ?

[ML Explained @mlexplained]

600k GPUs but still ran out of memory loading your mom’s weight

[Yam Peleg @Yampeleg]

Zuck:

1. LLaMA 3 is training.

2. Will be released open source.

3. Meta is buying 350,000 H100.
(Price: ~10.5$ billion)

4. Meta aims for AGI.

Let’s go!!

[ML Explained @mlexplained]

Learn to Build your own custom loss function in catboost

#MachineLearning

https://t.co/3KSs4wvplC

[ML Explained @mlexplained]

How to use #GPT4Turbo vision API.

https://t.co/a5CacsjUM4

#OpenAIDevDay

[ML Explained @mlexplained]

Pandas Tricks That You Must Know and Start Using https://t.co/BgFVNrrdjZ via @YouTube

[ML Explained @mlexplained]

How a False Positive Almost Ended The World https://t.co/e695lK1W8e via @YouTube

[ML Explained @mlexplained]

Sorry Jesus, but no walking on the water in @MuseeLouvre

[ML Explained @mlexplained]

Community notes got no chill.

They ran an ad on Twitter and got owned by a feature of the app only.

[ML Explained @mlexplained]

As Data Scientists, we all have to label data from time to time. So in this tutorial, I go over how you can build a quick Machine Learning Labelling Tool Using @Gradio by @huggingface in under 3 minutes.
https://t.co/gqynVe7WyG via @YouTube

[ML Explained @mlexplained]

This scene encapsulates what happens in PEFT with LoRA.
Explaining AI with Hera Pheri memes

[ML Explained @mlexplained]

Deep Learning Models are yet to conquer tabular data. Xgboost usually outperforms the best deep learning models when it comes to tabular data.

[ML Explained @mlexplained]

#Chandrayaan3

[ML Explained @mlexplained]

Watching model training dashboards is always satisfying

[ML Explained @mlexplained]

Data Science is mostly data cleaning. Cleaning your data yields more benefits with a simpler model than unclean data will do with state of the art models

[ML Explained @mlexplained]

The way to deploy on spaces is very simple. All you’ve to do is create your
1. https://t.co/wlEvIsznsM - This is where your app resides
2. requirements.txt - If you want to load in a packages that aren’t loaded by default
3. Add your model if it’s stored as bin or pickle

[ML Explained @mlexplained]

Take your ML models to the next level by deploying them on Spaces by @huggingface using @Gradio

In this video I go over how you can deploy your ML model within minutes using Gradio on Spaces

https://t.co/PMf0Utkt7E

[ML Explained @mlexplained]

In case you want to read it as an article.

https://t.co/y7aLCW6Jst

[ML Explained @mlexplained]

In case one doesn't want to read the article, this is the accompanying video -
https://t.co/XfKMs0SkzO

[ML Explained @mlexplained]

This is a more beginner-friendly article I've written.
Learn about MLaas (Machine Learning as a service). https://t.co/Okr80X2wmZ