Alternatives and similar repositories for optimizers

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

• etcrago / Tutorial-Arima-w-jeffrey-yau
  ☆98Updated 6 years ago
• tirthajyoti / Optimization-Python
  General optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python
  ☆229Updated 3 years ago
• benalexkeen / Introduction-to-linear-programming
  Introduction to Linear Programming with Python
  ☆179Updated 5 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆104Updated 3 years ago
• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 8 years ago
• aprilypchen / depy2016
  ☆110Updated 9 years ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 6 years ago
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆275Updated 8 years ago
• plotly / dash-oil-and-gas-demo
  Dash Demo App - New York Oil and Gas
  ☆193Updated last year
• fonnesbeck / intro_stat_modeling_2017
  Introduction to Statistical Modeling with Python (PyCon 2017)
  ☆168Updated 4 years ago
• dziganto / Data_Science_Fundamentals
  ☆101Updated 7 years ago
• TomAugspurger / pandas-head-to-tail
  ☆86Updated 7 years ago
• rouseguy / TimeSeriesAnalysiswithPython
  Time Series Analysis with Python
  ☆347Updated 9 years ago
• IBMDecisionOptimization / tutorials
  ☆45Updated 4 years ago
• Pierian-Data / AutoArima-Time-Series-Blog
  This is the code notebook for the blog post on using Python and Auto ARIMA
  ☆104Updated 5 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated 10 months ago
• mnguyenngo / ab-framework
  Notes and Python scripts for A/B or Split Testing
  ☆140Updated 2 years ago
• urgedata / pythondata
  repo for code published on pythondata.com
  ☆123Updated 6 years ago
• rasmusab / bayesianprobabilitiesworkshop
  A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.
  ☆124Updated 3 years ago
• Apress / mastering-ml-w-python-in-six-steps
  Source code for 'Mastering Machine Learning with Python in Six Steps' by Manohar Swamynathan
  ☆111Updated 8 years ago
• shellshock1911 / Sky-Cast-Capstone
  Sky Cast: A Comparison of Modern Techniques for Forecasting Time Series
  ☆68Updated 7 years ago
• khanhnamle1994 / applied-machine-learning
  A step-by-step guide to get started with Applied Machine Learning
  ☆140Updated 6 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• alysivji / talks
  Code, slides, and documentation for the talks I have given.
  ☆113Updated last month
• s-heisler / pycon2017-optimizing-pandas
  Materials for PyCon 2017 presentation on optimizing Pandas code
  ☆213Updated 5 years ago
• gakhov / pycon-ua-2018
  Talk at PyCon UA 2018 (Kharkov, Ukraine)
  ☆64Updated 7 years ago
• seanabu / seanabu.github.io
  personal blog
  ☆107Updated 6 years ago
• trangel / stats-with-python
  Learning statistics with Python
  ☆53Updated 4 years ago
• SimiY / pydata-sf-2016-arima-tutorial
  PyData San Francisco 2016 - ARIMA Tutorial
  ☆86Updated 8 years ago
• bgweber / StartupDataScience
  ☆293Updated 6 years ago