Questions tagged [mlops]
The mlops tag has no usage guidance.
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Hugging Face Real Time Object Detection Deployment
I'm developing a live object detection app using Streamlit and the YOLOv8 model. The app runs smoothly with real-time inference on my local machine. However, when I deploy it to Hugging Face Spaces, ...
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Which ML models can be saved using HDF5?
I've read that HDF5 format can be used to save machine learning models. However, when using a trained CNNClassifier instance from ...
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Prompt Ops Alternatives
What are the main alternatives for prompt ops nowadays? By prompt ops, I mean a comprehensive solution for tracking prompt engineering experiments and also registering prompts in different stages, ...
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How to migrate my ML Model from Staging to Prod without having to retrain the model and without lossing the hyperparameters
I want to train my ML model in my staging environment and then push the model to production if it performs well. However, I do not want to retrain the model on the entire dataset. I simply want to ...
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Best cloud provider for Computer Vision in 2024. (Market relevant)
So I am currently unemployed, I am an ML engineer, Computer Vision focused.
I have experience with many cloud providers but no certifications. Generally job postings will ask for experience/...
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Integrating MLFlow and SageMaker for a More Robust ML Model Deployment Pipeline
I'm seeking advice on enhancing the deployment pipeline of a machine learning model that's accessed via a FastApi in production. My goal is to replace the existing setup with a more robust and ...
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Should I apply the same data transformations in production for my classification model's inference steps
I am now moving my best classification model to production and doing tests currently.
Should I use the same scaler() I used in training during my inference in ...
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Preprocessing overheads in Machine Learning
Meta reports that data preprocessing overheads is fast becoming a bottleneck to machine learning training (https://engineering.fb.com/2022/09/19/ml-applications/data-ingestion-machine-learning-...
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256
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Training a CNN in production on new data
How should I approach training a convolutional neural network in production on new data when I detect model performance degradation due to data or concept drift? Resources like this one and this one ...
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What is the difference between Covariate Shift, Label Shift, Concept Shift, Concept Drift, and Prior Probability Shift?
As a beginner in MLOps, I was overwhelmed by some confusing definitions.
As far as I understand, when we have a classifier or regressor with y = f(X) function:
<...
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204
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Can I use Population Stability Index (PSI) when observations have multiple variables?
I understand from resources like this one that the Population Stability Index (PSI) can be used to test for data drift when a machine learning model is in production. However, the resources I have ...
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Sustain learning separately - continuous learning
This question is to seek suggestions on how to architect the continuous learning approach in distributed manner. Let me explain the situation:
In my classification problem, I have classes which can ...
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How is model scheduling set up in practice?
I have been working on various machine learning models so far, but never yet on the deployment phase of an ML project. I have vaguely used Apache Airflow and I'm aware that it is a tool for scheduling ...
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642
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How to Combat Data Drift
I have customer demographic data that include columns like: age, the first half of the postcode, occupation (there is a defined list of possible occupations), and more. Each month I get a new batch of ...
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223
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AWS Stepfunctions using SageMaker ScriptProcessor
Hello Data Science/Engineer folks,
I need a help in orchestrating a ML model using AWS Step Functions. There are some tutorials on using StepFunction with Python SDKs, but all of them are focused ...
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Automate Clustering predictions and RFM metrics
We did a POC for customer segmentation and followed the below approach
a) extract data from source system (SAP business objects)
b) Use python jupyter notebook to manipulate, merge and group data (...
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MLOps for beginner
I am 1 year old in ML and have been using jupyter notebook to build static models all these days, do some analysis and present my results to the bosses as it was all POC.
Now, we would like to scale ...
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Meaningfully compare target vs observed TPR & FPR
Suppose I have a binary classifier $f$ which acts on an input $x$. Given a threshold $t$, the predicted binary output is defined as:
$$
\widehat{y} = \begin{cases}
1, & f(x) \geq t \\
0, &...
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How is model evaluation and re-training done after deployment without ground truth labels?
Suppose I deployed a model by manual labeling the ground truth labels with my training data, as the use case is such that there's no way to get the ground truth labels without humans. Once the model ...
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What is MLOPS - Why & How to get started?
MLOPs has been gaining traction and a lot of fortune 500 companies are creating team specifically for MLOPs.Can anyone help me understand?
Why MLOPs is gaining so much traction?
How it is different ...
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197
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Data preprocessing framework/library alternatives
I am currently working on some python machine learning projects that are soon to be deployed to production. As such, in our team we are interested in doing this the most "correct" way, ...
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How do I verify and test a machine learning model against reality during time?
As a software engineers we familiar with a concept of testing (unit, integration, e2e) Tests give us a level of confidence about the code and changes in our code.
Looks like for ML the "code"...
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Is my idea of a Feature Store wrong?
Cross-posted on Reddit ML.
Should a Feature Store be part of an enterprise data catalog?
To me, a feature store seems to be a highly niche data catalog but missing a lot of the benefits of having an ...
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What features used by CNN model should a feature store actually store? [closed]
According to MLOPs principle, it is recommended to have a feature store. The question is in the context of doing image classification using deep learning models like convolutional neural networks ...
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MLflow real world experience
Can someone provide a summary of the real world deployment experience of MLflow? We have a few ML models (e.g., LightGBM, tensorflow v2, etc.) and want to avoid framework like SageMaker (due to ...
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