tonyleidong / OptimalFlow
OptimalFlow is an omni-ensemble and scalable automated machine learning Python toolkit, which uses Pipeline Cluster Traversal Experiments(PCTE) and Selection-based Feature Preprocessor with Ensemble Encoding(SPEE), to help data scientists build optimal models, and automate supervised learning workflow with simpler coding.
β27Updated last year
Alternatives and similar repositories for OptimalFlow:
Users that are interested in OptimalFlow are comparing it to the libraries listed below
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API πβ53Updated 3 years ago
- NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for β¦β107Updated 3 years ago
- Predict the poverty of households in Costa Rica using automated feature engineering.β23Updated 4 years ago
- A scikit-learn compatible estimator based on business-rules with interactive dashboard includedβ28Updated 3 years ago
- Automated Data Science and Machine Learning library to optimize workflow.β104Updated 2 years ago
- Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & trackingβ55Updated 3 years ago
- Automated Transparent Genetic Feature Engineeringβ22Updated last year
- Instant search for and access to many datasets in Pyspark.β34Updated 2 years ago
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.β65Updated 3 months ago
- CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning systemβ77Updated 2 years ago
- ForML - A development framework and MLOps platform for the lifecycle management of data science projectsβ106Updated last year
- XAI Stories. Case studies for eXplainable Artificial Intelligenceβ29Updated 4 years ago
- FairPut - Machine Learning Fairness Framework with LightGBM β Explainability, Robustness, Fairness (by @firmai)β71Updated 3 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python libraryβ51Updated 2 years ago
- Repo for PyData 2019 Tutorial - New Trends in Estimation and Inferenceβ25Updated 5 years ago
- Python implementation of R package breakDownβ42Updated last year
- Smart, automatic detection and stationarization of non-stationary time series data.β29Updated 2 years ago
- β21Updated last year
- Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.β51Updated last year
- β12Updated 4 years ago
- Better `keras` models for time series and beyondβ61Updated last year
- Guide for applying Unit Testing in data-driven projectsβ19Updated 4 years ago
- Work for Mastering Large Datasets with Pythonβ19Updated 2 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019β41Updated 9 months ago
- Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networksβ25Updated 5 years ago
- Distributed, large-scale, benchmarking framework for rigorous assessment of automatic machine learning repositories, projects, and librarβ¦β30Updated 2 years ago
- Practical ideas on securing machine learning modelsβ36Updated 3 years ago
- Helpers for scikit learnβ16Updated 2 years ago
- AutoBazaar: An AutoML System from the Machine Learning Bazaarβ33Updated 3 years ago
- Companion Notebooks and Data for Data Science with Python and Dask from Manning Publicationsβ52Updated 4 years ago