Tf2 serving

Load dataset

Model server tester

Tf2 serving v2

SQL To File - Ingest data using SQL query

Sql to file

Select features through multiple Statistical and Model filters

Feature selection

Rolling aggregation over Metrics and Lables according to specifications

Aggregate

Bert embeddings

Describe

Model server

Create Pandas Profiling Report from Dataset

Pandas profiling report

Load dask

Slack notify

Xgb serving

Model monitoring batch

Saves a stream to Parquet and can lunch drift detection task on it

Stream to parquet

Describe spark

Create a binary classification sample dataset and save.

Gen class data

Open a file/object archive into a target directory

Open archive

Send email

Deploy a streaming Concept Drift detector on a labeled stream

Concept drift

BERT based sentiment classification model

Sentiment analysis serving

Tf1 serving

Churn server

Model monitoring stream

Compute drift magnitude between Time-Samples T and U

Virtual drift

deploy an rnn based stock analysis model server.

Rnn serving

estimate feature importances using permutations

Feature perms

V2 model tester

Coxph test

retrieve remote archive, open and save as parquet

Arc to parquet

Github utils

V2 model server

Deploy a streaming Concept Drift detector on a labeled stream. the nuclio part of the concept_drift function

Concept drift streaming

ONNX intigration in MLRun, some utils functions for the ONNX framework, optimizing and converting models from different framework to ONNX using MLRun.

Onnx utils

Feature Store ingest function that runs the transformation graph on the source of the featureset.

Ingest

Get offline features

Azure AutoML integration in MLRun, including utils functions for training models on Azure AutoML platfrom.

Azureml utils

Automatic train, evaluate and predict functions for the ML frameworks - Scikit-Learn, XGBoost and LightGBM.

Auto trainer

Snowflake Dask - Ingest snowflake data in parallel with Dask cluster

Snowflake dask

Azureml serving

Batch inference (also knows as prediction) for the common ML frameworks (SciKit-Learn, XGBoost and LightGBM) while performing data drift analysis.

Batch inference

Hugging face serving

Automatic train and optimize functions for HuggingFace framework

Hugging face classifier trainer

Validate a dataset using Great Expectations

Validate great expectations

Transcribe

GenAI approach of question answering on a given data

Question answering

Huggingface auto trainer

This function is used to recognize PII in a directory of text files

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Function hub