Alternatives and similar repositories for tds_you_dont_need_statistics_to_run_experiments

Users that are interested in tds_you_dont_need_statistics_to_run_experiments are comparing it to the libraries listed below

• AutoViML / lazytransform
  Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.
  ☆65Updated 7 months ago
• formlio / forml
  ForML - A development framework and MLOps platform for the lifecycle management of data science projects
  ☆106Updated 2 years ago
• tlentali / leab
  📈🔍 Lets Python do AB testing analysis.
  ☆78Updated 5 months ago
• elleobrien / automatic_testing
  ☆21Updated 2 years ago
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆27Updated 3 years ago
• data-max-hq / ab-testing-in-ml
  Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.
  ☆40Updated 8 months ago
• zenml-io / zenml-gitflow
  A repository that showcases how you can use ZenML with Git
  ☆70Updated last month
• bishwarup307 / async-ml-medium
  Collection of python scripts to demonstrate asynchronous programming in python
  ☆11Updated 3 years ago
• cvs-health / aequilibrium
  Package designed for handling imbalanced classification
  ☆18Updated last year
• NITRO-AI / NitroFE
  NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for …
  ☆108Updated 3 years ago
• hsbc / tslumen
  A library for Time Series EDA (exploratory data analysis)
  ☆71Updated last year
• ml-for-high-risk-apps-book / Machine-Learning-for-High-Risk-Applications-Book
  Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
  ☆102Updated 2 years ago
• Spratiher9 / Sparkora
  Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟
  ☆53Updated 3 years ago
• donlapark / coverforest
  A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.
  ☆45Updated last month
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆50Updated last year
• khuyentran1401 / pretty-print-confusion-matrix
  Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
  ☆19Updated 3 years ago
• edublancas / ml-testing
  🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects
  ☆82Updated 3 years ago
• bodywork-ml / ml-pipeline-engineering
  Best practices for engineering ML pipelines.
  ☆36Updated 3 years ago
• tblume1992 / MFLES
  ☆115Updated last year
• koaning / scikit-churn
  Exploring some issues related to churn
  ☆17Updated last year
• AutoViML / pandas_dq
  Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
  ☆132Updated last year
• jacopotagliabue / no-ops-machine-learning
  A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.
  ☆37Updated 4 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆61Updated 2 years ago
• kweinmeister / notebooks
  Jupyter notebooks for learning and demonstrations
  ☆18Updated last month
• Elysian01 / Data-Purifier
  A Python library for Automated Exploratory Data Analysis, Automated Data Cleaning, and Automated Data Preprocessing For Machine Learning …
  ☆45Updated 3 years ago
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆90Updated last year
• decile-team / spear
  SPEAR: Programmatically label and build training data quickly.
  ☆108Updated last year
• causalens / cai-causal-graph
  A Causal AI package for causal graphs.
  ☆60Updated 5 months ago
• smazzanti / valicast
  Validation for forecasts
  ☆18Updated 2 years ago
• ben-arnao / StoRM
  A neural network hyper parameter tuner
  ☆30Updated last year