catalog.yaml

aggregate:
  categories:
  - data-prep
  description: Rolling aggregation over Metrics and Lables according to specifications
  docfile: aggregate/aggregate.ipynb
  kind: job
  versions:
    latest: aggregate/function.yaml
arc-to-parquet:
  categories:
  - data-movement
  - utils
  description: retrieve remote archive, open and save as parquet
  docfile: arc_to_parquet/arc_to_parquet.ipynb
  kind: job
  versions:
    latest: arc_to_parquet/function.yaml
bert-embeddings:
  categories:
  - NLP
  - BERT
  - embeddings
  description: Get BERT based embeddings for given text
  docfile: bert_embeddings/bert_embeddings.ipynb
  kind: remote
  versions:
    latest: bert_embeddings/function.yaml
churn-server:
  categories:
  - serving
  - ml
  description: churn classification and predictor
  docfile: churn_server/churn_server.ipynb
  kind: serving
  versions:
    latest: churn_server/function.yaml
concept-drift:
  categories:
  - ml
  - serve
  description: Deploy a streaming Concept Drift detector on a labeled stream
  docfile: concept_drift/concept_drift.ipynb
  kind: job
  versions:
    latest: concept_drift/function.yaml
concept-drift-streaming:
  categories:
  - ml
  - serve
  description: Deploy a streaming Concept Drift detector on a labeled stream. the
    nuclio part of the concept_drift function
  docfile: concept_drift_streaming/concept_drift_streaming.ipynb
  kind: remote
  versions:
    latest: concept_drift_streaming/function.yaml
coxph-test:
  categories:
  - ml
  - test
  description: Test cox proportional hazards model
  docfile: coxph_test/coxph_test.ipynb
  kind: job
  versions:
    latest: coxph_test/function.yaml
coxph-trainer:
  categories:
  - training
  - ml
  description: cox proportional hazards, kaplan meier plots
  docfile: coxph_trainer/coxph_trainer.ipynb
  kind: job
  versions:
    latest: coxph_trainer/function.yaml
describe:
  categories:
  - analysis
  description: describe and visualizes dataset stats
  docfile: describe/describe.ipynb
  kind: job
  versions:
    latest: describe/function.yaml
describe-dask:
  categories:
  - analysis
  description: describe and visualizes dataset stats
  docfile: describe_dask/describe_dask.ipynb
  kind: job
  versions:
    latest: describe_dask/function.yaml
describe-spark:
  categories: []
  description: ''
  docfile: describe_spark/describe_spark.ipynb
  kind: job
  versions:
    latest: describe_spark/function.yaml
feature-perms:
  categories:
  - analysis
  description: estimate feature importances using permutations
  docfile: feature_perms/feature_perms.ipynb
  kind: job
  versions:
    latest: feature_perms/function.yaml
feature-selection:
  categories:
  - data-prep
  - ml
  description: Select features through multiple Statistical and Model filters
  docfile: feature_selection/feature_selection.ipynb
  kind: job
  versions:
    latest: feature_selection/function.yaml
gen-class-data:
  categories:
  - data-prep
  description: Create a binary classification sample dataset and save.
  docfile: gen_class_data/gen_class_data.ipynb
  kind: job
  versions:
    latest: gen_class_data/function.yaml
github-utils:
  categories:
  - notifications
  - utils
  description: add comments to github pull request
  docfile: github_utils/github_utils.ipynb
  kind: job
  versions:
    latest: github_utils/function.yaml
load-dask:
  categories:
  - data-movement
  - utils
  description: load dask cluster with data
  docfile: load_dask/load_dask.ipynb
  kind: dask
  versions:
    latest: load_dask/function.yaml
load-dataset:
  categories:
  - data-source
  - ml
  description: load a toy dataset from scikit-learn
  docfile: load_dataset/load_dataset.ipynb
  kind: job
  versions:
    latest: load_dataset/function.yaml
model-monitoring-batch:
  categories: []
  description: ''
  docfile: model_monitoring_batch/model_monitoring_batch.ipynb
  kind: job
  versions:
    latest: model_monitoring_batch/function.yaml
model-monitoring-stream:
  categories: []
  description: ''
  docfile: model_monitoring_stream/model_monitoring_stream.ipynb
  kind: remote
  versions:
    latest: model_monitoring_stream/function.yaml
model-server:
  categories:
  - serving
  - ml
  description: generic sklearn model server
  docfile: model_server/model_server.ipynb
  kind: remote
  versions:
    latest: model_server/function.yaml
model-server-tester:
  categories:
  - ml
  - test
  description: test model servers
  docfile: model_server_tester/model_server_tester.ipynb
  kind: job
  versions:
    latest: model_server_tester/function.yaml
open-archive:
  categories:
  - data-movement
  - utils
  description: Open a file/object archive into a target directory
  docfile: open_archive/open_archive.ipynb
  kind: job
  versions:
    latest: open_archive/function.yaml
pandas-profiling-report:
  categories:
  - analysis
  description: Create Pandas Profiling Report from Dataset
  docfile: pandas_profiling_report/pandas_profiling_report.ipynb
  kind: job
  versions:
    latest: pandas_profiling_report/function.yaml
project-runner:
  categories:
  - utils
  description: Nuclio based - Cron scheduler for running your MLRun projects
  docfile: project_runner/project_runner.ipynb
  kind: remote
  versions:
    latest: project_runner/function.yaml
rnn-serving:
  categories:
  - model-serving
  description: deploy an rnn based stock analysis model server.
  docfile: rnn_serving/rnn_serving.ipynb
  kind: serving
  versions:
    latest: rnn_serving/function.yaml
send-email:
  categories:
  - notifications
  description: Send Email messages through SMTP server
  docfile: send_email/send_email.ipynb
  kind: job
  versions:
    latest: send_email/function.yaml
sentiment-analysis-serving:
  categories:
  - serving
  - NLP
  - BERT
  - sentiment analysis
  description: BERT based sentiment classification model
  docfile: sentiment_analysis_serving/sentiment_analysis_serving.ipynb
  kind: serving
  versions:
    latest: sentiment_analysis_serving/function.yaml
sklearn-classifier:
  categories:
  - ml
  - training
  description: train any classifier using scikit-learn's API
  docfile: sklearn_classifier/sklearn_classifier.ipynb
  kind: job
  versions:
    latest: sklearn_classifier/function.yaml
sklearn-classifier-dask:
  categories:
  - ml
  - training
  - dask
  description: train any classifier using scikit-learn's API over Dask
  docfile: sklearn_classifier_dask/sklearn_classifier_dask.ipynb
  kind: job
  versions:
    latest: sklearn_classifier_dask/function.yaml
slack-notify:
  categories:
  - ops
  description: Send Slack notification
  docfile: slack_notify/slack_notify.ipynb
  kind: job
  versions:
    latest: slack_notify/function.yaml
spark-submit:
  categories: []
  description: ''
  docfile: spark_submit/spark_submit.ipynb
  kind: job
  versions:
    latest: spark_submit/function.yaml
sql-to-file:
  categories:
  - data-prep
  description: SQL To File - Ingest data using SQL query
  docfile: sql_to_file/sql_to_file.ipynb
  kind: job
  versions:
    latest: sql_to_file/function.yaml
stream-to-parquet:
  categories:
  - ml
  - serve
  description: Saves a stream to Parquet and can lunch drift detection task on it
  docfile: stream_to_parquet/stream_to_parquet.ipynb
  kind: remote
  versions:
    latest: stream_to_parquet/function.yaml
test-classifier:
  categories:
  - ml
  - test
  description: test a classifier using held-out or new data
  docfile: test_classifier/test_classifier.ipynb
  kind: job
  versions:
    latest: test_classifier/function.yaml
tf1-serving:
  categories:
  - serving
  - dl
  description: tf1 image classification server
  docfile: tf1_serving/tf1_serving.ipynb
  kind: remote
  versions:
    latest: tf1_serving/function.yaml
tf2-serving:
  categories:
  - serving
  - dl
  description: tf2 image classification server
  docfile: tf2_serving/tf2_serving.ipynb
  kind: remote
  versions:
    latest: tf2_serving/function.yaml
tf2-serving-v2:
  categories:
  - serving
  - dl
  description: tf2 image classification server v2
  docfile: tf2_serving_v2/tf2_serving_v2.ipynb
  kind: serving
  versions:
    latest: tf2_serving_v2/function.yaml
v2-model-server:
  categories:
  - serving
  - ml
  description: generic sklearn model server
  docfile: v2_model_server/v2_model_server.ipynb
  kind: serving
  versions:
    latest: v2_model_server/function.yaml
v2-model-tester:
  categories:
  - ml
  - test
  description: test v2 model servers
  docfile: v2_model_tester/v2_model_tester.ipynb
  kind: job
  versions:
    latest: v2_model_tester/function.yaml
virtual-drift:
  categories:
  - ml
  - serve
  - concept-drift
  description: Compute drift magnitude between Time-Samples T and U
  docfile: virtual_drift/virtual_drift.ipynb
  kind: job
  versions:
    latest: virtual_drift/function.yaml
xgb-custom:
  categories:
  - model-testing
  description: simulate data with outliers.
  docfile: xgb_custom/xgb_custom.ipynb
  kind: job
  versions:
    latest: xgb_custom/function.yaml
xgb-serving:
  categories:
  - model-serving
  description: deploy an XGBoost model server.
  docfile: xgb_serving/xgb_serving.ipynb
  kind: remote
  versions:
    latest: xgb_serving/function.yaml
xgb-test:
  categories:
  - model-test
  description: Test one or more classifier models against held-out dataset.
  docfile: xgb_test/xgb_test.ipynb
  kind: job
  versions:
    latest: xgb_test/function.yaml
xgb-trainer:
  categories:
  - model-prep
  description: train multiple model types using xgboost.
  docfile: xgb_trainer/xgb_trainer.ipynb
  kind: job
  versions:
    latest: xgb_trainer/function.yaml