Questions tagged [deployment]
The deployment tag has no usage guidance.
17
questions
4
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2
answers
816
views
Do model training pipeline should run on dev, staging and production environment?
I know it's a best practice to ship our code from dev to staging to production by including different level tests and validations that will help to confidently deploy on the production environment.
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1
vote
1
answer
26
views
Ways to share Pytorch model without revealing architecture?
We are trying to give a model to collaborators but would like to protect the IP. What are some ways to encrypt/hide/compile the definition when sharing a trained model?
1
vote
1
answer
23
views
What is the best approach to deploy N number of ML models as a scalable service in the Cloud?
I've N (~50) number of sentiment models of different languages, which were fine tuned on HggingFace's transformer models. Each of the models as 2-3 GB in size approx. Now, how can I deploy all these ...
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0
answers
8
views
Can accuracy improve when there is evidence of domain-shift between training and deployment?
A model for image analysis was trained using data captured with imaging system A. I then deployed the model on imaging system B. System B has better image contrast than system A. Features in the last ...
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0
answers
88
views
How to use early_stopping_rounds in the Final Model? (CatBoost example with Optuna)
Imagine we have a model in the sklearn pipeline:
...
0
votes
2
answers
44
views
Which random_state to use in test_train_split when deploying final model?
I have developed a Random Forest that gives varying results depending on the random state of the test train split. This is normal, because a lot of the values in the data are extreme, without being ...
0
votes
1
answer
21
views
After experimentation, how do we learn a final model for deployment?
I have a question regarding learning a "final" model for deployment. Assuming my task is a classification one, my workflow during experimentation is as follows.
Get the data: ...
0
votes
0
answers
2k
views
ValueError: dtype='numeric' is not compatible with arrays of bytes/strings.Convert your data to numeric values explicitly instead
I am new to machine learning model deployment. In a sequence, local system rises an error while running "app.py" file, that is:
...
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0
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29
views
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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0
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9
views
Shadow deployment vs batch prediction on log?
In shadow deployment we 1) deploy a new model in parallel with the existing one; 2) route every incoming request to both the existing and candidate model; 3) serve the existing model's predictions for ...
1
vote
0
answers
5
views
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 ...
0
votes
0
answers
401
views
How To Scale a multiple columns using a MinMaxScaler() using the pickled file during deployment of the model?
I am trying to deploy an ml model. As a part of processing the data, I am scaling my data. I pickled the scaler and need to do the same in my deployment code. But I am not able to do it correctly.
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1k
views
FileNotFoundError: Unsuccessful TensorSliceReader constructor
I am trying to deploy my model. I am encountering the following problem:
FileNotFoundError: Unsuccessful TensorSliceReader constructor: Failed
to find any matching files for
ram://a603e930-4fda-4105-...
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votes
0
answers
6
views
Deploying Azure ML Web Service in Flask
I have trained a predictive model on Azure ML Studio, and deployed it as a web service. I have the API key Azure ML gave me. I want to take user input on my own Flask app and get the prediction from ...
0
votes
0
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39
views
Deploy ML model on java web server or on python web application
Newbie here and I only have experience in training machine learning models on Jupyter notebook along with test/validate the model accuracy.
I would like to move on and learn how I can deploy machine ...
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35
views
How to create recommendation systems that are suitable for deployment in production environment for an ecommerce giant?
I am making a recommendation model for an ecommerce client that has huge number of products of various categories. Product data set can be considered similar to that of Amazon. For now, I am starting ...
1
vote
1
answer
144
views
How to handle categorical feature engineering in ML production?
I have a classification dataset ,where I have a lot of categorical columns .
I have one hot encoded ie. dummy variables in my training .
How to handle this in production side of ML. There are cases ...