Yusuke Minami

causallift. CausalLift: Python package for causality-based Uplift Modeling in real-world business

pipelinex. PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

Python_Packages_for_Pipeline_Workflow. This article compares open-source Python packages for pipeline/workflow development: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX.

optkeras. OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

scrape-pdf-financial-reports. Jupyter Notebook

kedro-starters-sklearn. Kedro starter templates using Scikit-learn and optionally MLflow

Tools_for_ML_Lifecycle_Management. Comparison of ML Life Cycle Management (Experiment Tracking, Model Management, etc.): MLflow, DVC, Pachyderm, Sacred, Polyaxon, Allegro Trains, VertaAI ModelDB, Kubeflow Katib, Guild AI, Kubeflow Metadata, Weights & Biases, Neptune.ai, Valohai, Comet

kaggle_nfl. A solution for Kaggle NFL Big Data Bowl competition using PipelineX

pipelinex_causallift. Uplift Modeling project using PipelineX and CausalLift

pipelinex_image_processing. A project to use PipelineX for image processing

RingFit_MegaMan. Instruction to play Mega Man (known as Rockman in Japan) using Ring Fit Adventure controller for exercise

kedro_mlflow. A simple example project using Kedro 0.16.x, MLflow, and PipelineX to run Scikit-learn tasks.

DCRNN. Jupyter Notebook

pipelinex_sklearn. A simple example project using Kedro, MLflow, and PipelineX to run Scikit-learn tasks.

awesome-dataset-annotations. Sample dataset annotations for Vision and Language tasks

kedro_template. Python

pipelinex_template. Template project for PipelineX

flatten-dict. A flexible utility for flattening and unflattening dict-like objects in Python.

ML_frameworks. Summary of Python frameworks for Machine Learning projects

pyminyus. Python utility

kedro-viz. Visualise your Kedro data pipelines

ml_config. ML and MLOps configuration (Docker and rc files)

utils. Python

export-ipynb. Python

Minyus.

pylift. Uplift modeling package.

off-policy-evaluation-doc. CSS