Explore how to design a #MachineLearning pipeline with built-in observability for credit card fraud detection.

The approach leverages powerful tools like MLflow, Streamlit, Prometheus, Grafana & Evidently AI.

#InfoQ article: https://bit.ly/4l0FrBa

Mastering LLM Fine-Tuning: Harnessing SkyPilot and MLflow for Seamless Training

In the fast-evolving world of machine learning, the ability to efficiently fine-tune Large Language Models (LLMs) is paramount. This article explores how to leverage SkyPilot and MLflow, two powerful ...

https://news.lavx.hu/article/mastering-llm-fine-tuning-harnessing-skypilot-and-mlflow-for-seamless-training

Live coding #mlflow

Nuevo Meetup de #PyData #Granada

Y van

#Python + #R en #Oncología / Aprende #MLFlow

Amalia y Daniel cerrarán este intenso año 2024 con una edición prenavideña el próximo de DICIEMBRE a las 19h en la sede de #ELCA

Calle Andrés Segovia 53, 3B · Granada

Apuntáos ya!

https://www.meetup.com/es-ES/pydatagrx/events/304896778

I just did my first project using the #mlflow library to track metrics on iterations of manual tuning of an #sklearn pipeline, it works great and gives me some idea of the search space before moving into automated hyperparameter tuning.

I am using it in a super basic way, as an alternative to creating a gazillion cells with comments tracking metrics, does anyone have any favorite features to check out for taking mlflow to the next level?
#machinelearning #python #MLOps #scikitlearn

MLflow LLM Evaluate：Amazon Bedrock / Claude 3.5 Sonnet で LLM-as-a-Judge による LLM の評価
https://qiita.com/nttd-saitouyun/items/061548eabe37a868c507?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

My blog post on "Building a Data Science Platform with Kubernetes" got published in Towards Data Science, explaining how to setup JupyterHub, MLflow and SeldonCore in Kubernetes

https://medium.com/towards-data-science/building-a-data-science-tool-stack-with-kubernetes-00c74b491b9d

Canonical Launches Data Science Stack for Data Science and Machine Learning Beginners #DataScienceStack #DSS #Datascience #MachineLearning #Ubuntu #Pytorch #Tensorflow #Microk8s #Jupyterlab #MLflow #Linux
https://ostechnix.com/canonical-data-science-stack-dss/

Hello friends!

These last two weeks in #mlopszoomcamp, a course organized by DataTalksClub, we finished the homework on #MLflow.
I have submitted your homework answers and the notebook has been uploaded to the repository.

For more details, see the module 3 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/03-orchestration

Thank you Alexey Grigorev for organizing the course.

Hello friends!

Thses last two weeks in #mlopszoomcamp, a course organized by DataTalksClub, we finished the homework on #MLflow.

For more details, see the module 3 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/03-orchestration

Thank you Alexey Grigorev for organizing the course.

Hello friends!

These last two weeks in #mlopszoomcamp, a course organized by DataTalksClub, we dive into the world of #MLflow.

For more details, check out the module 3 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/03-orchestration

Thank you Alexey Grigorev for organizing the course.

Hello friends!

This week in #mlopszoomcamp, a course organized by DataTalksClub, we finished the homework on #MLflow.
I have submitted your homework answers and the notebook has been uploaded to the repository.

For more details, see the module 2 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/02-experiment-tracking

Thank you Alexey Grigorev for organizing the course.

Hello friends!

This week in #mlopszoomcamp, a course organized by DataTalksClub, we finished the homework on #MLflow.

For more details, see the module 2 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/02-experiment-tracking

Thank you Alexey Grigorev for organizing the course.

Hello friends!

The last week in #mlopszoomcamp, a course organized by DataTalksClub, we dive into the world of #MLflow.

For more details, check out the module 2 course repository: https://github.com/DataTalksClub/mlops-zoomcamp/tree/main/02-experiment-tracking

Thank you Alexey Grigorev for organizing the course.

RAGのリトリーバ評価のための質問生成
https://qiita.com/taka_yayoi/items/a3c9d7c3be4d665a5341?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

Question about R, mlflow and models...

I am trying to register a R model using the crate flavor in mlflow, and I have some doubts.

I have been able to log and register the model. I have also tested that I can load the model again and use it for prediction (inputs/outputs are data.frames).

I was thinking... that would mean I should write the inference part in R, wouldn't it?

How could I deploy the model so it can be served as a general web service (REST API), not actually relying on final users to use R?

I'm now quite tired, but the only solution I have found is to maybe use plumbr to expose an API receiving a JSON with all the inputs as simple types, and generating the data.frame inside, as I have always done.

Do you think this can be done directly using a crated function? Has anybody done something similar?

Thanks in advance. I think this is a discussion worth having, as there is a lack of documentation on this topic for us R users. :(

I'm learning #mlflow for real for the first time and boy, I wish I was recording my reactions. Nothing makes sense!

Why am I getting this WARNING? Why are there little green and gray circles without tooltips? Why was this apparently successful run marked as "Failed"?

This is not a critique just on MLFlow. Software in general is often inscrutable and makes you feel stupid. After a while we get used to it and then write tutorials like "foo is easy, you just simply..."

MLflow Intro Course

Managing the Complete Machine Learning Lifecycle with MLflow is a three-hour intro to MLflow workshop by Jules S. Damji. The course is for beginners, and it covers the core functionality of MLflow:
Tracking
Projects
Models
Registry
UI

Playlist : https://www.youtube.com/playlist?list=PL2ivGIeWjZUhs_NX_xwR8yggvyB6wSnQh

Code : https://github.com/dmatrix/mlflow-workshop-part-1

I just published my first pypi package. I'm running #mlflow behind #Traefik with #Authelia for authentication and by default that doesn't work with mlflow client so I made a plugin.

https://pypi.org/project/mlflow-plugin-proxy-auth/

MLflow 2.8 with LLM-as-a-judge metrics and Best Practices for LLM Evaluation of RAG Applications #mlflow #ai #llm https://www.luisquintanilla.me/feed/mlflow-2-8-llm-as-judge-rag-evaluation?utm_medium=feed