Top Tweets for #serverlessml
gemma 4 on cloud run l4? sweet. but that serverless gpu cold start latency and cost per inference? serious tuning work there. #ServerlessML #GPUCloud
🚀🤖Serverless ML = hassle‑free deployments! No servers, no scaling headaches—just smooth, cost‑effective model serving with AWS Lambda, Azure Functions & GCP. ✨🙌
Follow my #365DaysOfAI journey👉https://t.co/bw3qMPbgEl | https://t.co/3DheYSU0vl
#ServerlessML #MachineLearning
Serverless ML for SLMs means true 'scale to zero, spike to millions,' slashing costs. This democratizes AI! How will YOU leverage this shift? Focus on cold start optimization.
#ServerlessML #SLMInference #CloudComputing #MachineLearning #Scalability #CostOptimization
Serverless architectures make it easy to deploy and update ML microservices.
With quick deployments, your time-to-market shortens, allowing for faster testing and iteration on ML models.
In today’s fast-paced world, the ability to deploy rapidly is critical.
#ServerlessML
"🚀 Just completed Module 9 of Serverless Deep Learning in #MLzoomcamp! 🧠💻 Exciting journey exploring the world of serverless ML. Thanks to @MLzoomcamp for this incredible course! 🙌 #MachineLearning #DeepLearning #ServerlessML"
They must have forgotten about the 30+ ML systems my students built on novel data sources with #serverlessml on @hopsworks at KTH last winter -
https://t.co/exCbCLI1cC
Serverless ML=MLOps- Infra.
What an informative session!🦾
#serverless #serverlessml #MLOps #serverlessahmedabad
Why do most ML courses only teach you with static data? Without new data, a model cannot generate any new value, it's dead. #serverlessml
https://t.co/CHFNtXiR3D
With #serverlessML, Data Scientists can easily deploy prediction services powered by machine learning using only Python. It's #MLOps without the Infra. You don't need to learn Kubernetes or Cloud Infrastructure to put ML in production.
More ⬇️
https://t.co/wrGdUmb29c
#ServerlessML is a new category of loosely coupled services that provide operational support for #AI products and services. Feature pipelines, training pipelines, and batch inference pipelines are orchestrated and run by serverless computing services.
I wrote this article to help me first understand by what i think serverless machine learning is and why I think it will unbundle many of the existing do-it-all ML platforms #serverlessml
https://t.co/4rJXGV0nOt
If you want to learn the basics of feature engineering with Python for tabular data in serverless ML systems, consider taking my self-paced free course on #serverlessml - https://t.co/9xvT81DaG5
Lecture 4 and lab 4 of the #serverlessml course are now out. Here, we cover serverless User Interfaces with @Gradio and @streamlit , deploying on https://t.co/OS8RSlmF6l.
Video and slides available here:
https://t.co/9xvT81DaG5
@agapow In my #serverlessml course, we cover 3 different UIs: Github Pages, Gradio, Streamlit. All can be served cost-free on cloud platforms.
https://t.co/9xvT81DaG5
@tylerjrichards @Ubunta @duckdb I cover streamlit in my #serverlessml course. Streamlit can provide the serverless UI for "prediction services" built on ML:
https://t.co/9xvT81DaG5
@s_ryz It's straightforward in Colab. I go through it in lab 2 in this #serverlessml course: (1) a python module in a subdir for your notebook, (2) a wheel, (3) a pypi library. You can pip install the wheel/pypi libs in your first notebook cells, then import. https://t.co/dNaasNMJf7
Lecture 3 of the #serverlessml course is out now. It covers feature selection, training pipelines, and the model registry. https://t.co/9xvT81l1rX
Lecture 2 of the #serverlessml course is out now. It covers the data modeling (star schema, obt) needed to build feature pipelines with data warehouses, the feature store, how to share feature logic between notebooks with python libraries:
https://t.co/9xvT81CCQx
The panel was awesome, talking about Machine Learning and Serverless.
@bianchiluca deserves to double as Serverless Hero and Machine Learning Hero.
Thanks to @Benoit_Boure @ryanjonesirl @atehrosius
and @paulchinjr for making it more fun.
#ServerlessML
https://t.co/yUt8EYjPkh
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