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SCIKIT-LEARN USER SURVEY
This survey is being conducted by the scikit-learn survey team to ensure that scikit-learn evolves in a way that benefits its user community.
Participation in this survey is voluntary and it offers an option to remain completely anonymous.
It should take approximately 15 minutes to complete.
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PROJECT FUTURE DIRECTION AND PRIORITIES
Thinking about scikit-learn's future, what aspects of the library would you prioritize for improvement?
A greater numerical value signifies a greater level of priority.
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8
Performance
Reliability
Packaging
New features
Technical documentation
Educational materials
Website redesign
Other
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8
Performance
Reliability
Packaging
New features
Technical documentation
Educational materials
Website redesign
Other
Clear selection
Please expand on your answer about the priorities for scikit-learn.
Your answer
What single immediate change to scikit-learn would bring the most value to you as a scikit-learn user?
Your answer
TECHNICAL QUESTIONS
PROJECT
Please order the following ML tasks in order of priority to you: (A higher number means higher priority)
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7
Regression
Classification
Forecasting
Outlier/anomaly detection
Dimensionality reduction
Clustering
Other
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2
3
4
5
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7
Regression
Classification
Forecasting
Outlier/anomaly detection
Dimensionality reduction
Clustering
Other
Clear selection
What visualizations do you use to evaluate your models? Select all that apply.
Confusion matrix
Reliability diagram
ROC curve
Precision-Recall curve
Feature importance
Residual plots
Learning curves
Other
Which DataFrame libraries do you use? Select all that apply.
cudf
Dask DataFrame
DuckDB
Modin
pandas
Polars
Spark DataFrame
Other
MODELING
What do you like the most about scikit-learn?
Your answer
Which other Machine Learning libraries do you use? Select all that apply.
CatBoost
Jax
Keras
LightGBM
PyTorch
Transformers
XGBoost
Other
Which estimators do you regularly use? Select all that apply.
LogisticRegression
RandomForestClassifier or RandomForestRegressor
HistGradientBoostingRegressor or HistGradientBoostingClassifier
Pipeline
ColumnTransformer
Other
Have you ever written your own estimator, or extended an existing scikit-learn estimator?
Choose
Yes
No
What ML features are important for your use case? Select all that apply.
Calibration of probabilistic classifiers
Calibration of regressors
Uncertainty estimates for prediction
Cost-sensitive learning
Feature importances
Sample weights
Metadata routing
Non-euclidean metrics
Is there additional information you want to pass to an estimator that is not X and Y?
Choose
Yes
No
If so, what kind of information would that be?
Your answer
How would it benefit the model training process?[
Your answer
DEPLOYMENT
Considering your current machine learning projects, how critical would GPU capabilities within scikit-learn be? (A higher number means it is very critical)
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3
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5
Clear selection
For model registry and experiment tracking, do you use any of the following tools? Select all that apply.
DVC
Neptune
MLFlow
Weight and biases
Custom tool
Other
For scheduling, do you use any of the following tools? Select all that apply.
Airflow
Argo
Coiled
Dagster
Kubeflow
Metaflow (outerbounds)
Custom tool
Other
How long does a typical model training take in your ML projects?
less than 10 seconds
less than a minute
less than 10 minutes
less than an hour
less than a day
more than a day
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4
5
More than 5
How many deployed models are you (and your team) currently maintaining?
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5
More than 5
How many deployed models are you (and your team) currently maintaining?
Clear selection
To what extent do you agree with the following statement?
Open source ML & AI frameworks and libraries are crucial for ensuring transparency and the reproducibility of AI research and development.
Choose
Strongly agree
Agree
Neither agree nor disagree
Disagree
Strongly Disagree
VOLUNTEER FOR INTERVIEW
Would you like to volunteer for a short conversation with the scikit-learn survey team to discuss your responses in more detail?
Choose
Yes
No
If yes, please provide your email address.
Your answer
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