Alternatives and similar repositories for Variable-Selection-Using-Python

Users that are interested in Variable-Selection-Using-Python are comparing it to the libraries listed below

• Sundar0989 / WOE-and-IV
  ☆136Updated 6 years ago
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆280Updated 8 years ago
• alteryx / predict-customer-churn
  A general-purpose framework for solving problems with machine learning applied to predicting customer churn
  ☆418Updated last year
• Sundar0989 / EndtoEnd---Predictive-modeling-using-Python
  ☆56Updated 6 years ago
• seanabu / seanabu.github.io
  personal blog
  ☆106Updated 7 years ago
• etcrago / Tutorial-Arima-w-jeffrey-yau
  ☆98Updated 6 years ago
• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 8 years ago
• rouseguy / TimeSeriesAnalysiswithPython
  Time Series Analysis with Python
  ☆348Updated 9 years ago
• mnguyenngo / ab-framework
  Notes and Python scripts for A/B or Split Testing
  ☆142Updated 3 years ago
• analyticalmonk / KMeans_elbow
  Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'
  ☆42Updated 4 months ago
• ParrotPrediction / docker-course-xgboost
  Materials for an online-course - "Practical XGBoost in Python"
  ☆219Updated 9 years ago
• WillKoehrsen / automated-feature-engineering
  Automated feature engineering in Python with Featuretools
  ☆520Updated 6 years ago
• amueller / scipy-2018-sklearn
  Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller
  ☆248Updated 6 years ago
• baumanab / udacity_ABTesting
  Project work for Udacity's AB Testing Course
  ☆83Updated 8 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• khanhnamle1994 / applied-machine-learning
  A step-by-step guide to get started with Applied Machine Learning
  ☆140Updated 7 years ago
• aprilypchen / depy2016
  ☆110Updated 9 years ago
• jphall663 / GWU_data_mining
  Materials for GWU DNSC 6279 and DNSC 6290.
  ☆240Updated 4 months ago
• justmarkham / awesome-machine-learning
  A curated list of awesome Machine Learning frameworks, libraries and software.
  ☆39Updated 9 years ago
• justmarkham / pycon-2018-tutorial
  Using pandas for Better (and Worse) Data Science
  ☆325Updated 6 years ago
• alteryx / predict-loan-repayment
  Predict whether a loan will be repaid using automated feature engineering.
  ☆64Updated 2 years ago
• Semantive / Kaggle-Demand-Forecasting-Models
  Demand Forecasting Models for Kaggle competition
  ☆85Updated 7 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• chrisluedtke / data-science-journal
  Personal repository of data science demonstrations and references
  ☆77Updated 2 years ago
• cmawer / pycon-2017-eda-tutorial
  Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"
  ☆237Updated 3 years ago
• WillKoehrsen / Bokeh-Python-Visualization
  A Bokeh project developed for learning and teaching Bokeh interactive plotting!
  ☆362Updated 4 years ago
• arstepanyan / Notes
  Notes from different sources such as Harvard CS109 course, Springboard's Data Science Interview questions, Elements of Programming Interv…
  ☆35Updated 5 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆454Updated 5 years ago
• maoting1223 / pycon_sg_2016
  PyCon SG 2016 - Customer Segmentation in Python
  ☆56Updated 9 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆105Updated 3 years ago