Alternatives and similar repositories for Image-Based-Airbnb-Pricing-Algorithm

Users that are interested in Image-Based-Airbnb-Pricing-Algorithm are comparing it to the libraries listed below

• AlexIoannides / notes-and-demos
  Study notes and demos.
  ☆12Updated last year
• SimonOuellette35 / PyData-talk---Intro-to-PyMC3
  Companion code for my PyData talk: "Introduction to Probabilistic Programming with PyMC3"
  ☆13Updated 6 years ago
• AlexIoannides / lime-interpretable-ml
  An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learn…
  ☆15Updated 6 years ago
• canyon289 / causal_inf_bookclub
  Supporting material for the book club
  ☆15Updated 2 years ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆49Updated 3 years ago
• DiegoUsaiUK / Propensity_Modelling
  Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
  ☆27Updated 2 years ago
• aslakey / CBM_Encoding
  CBM Encoding
  ☆19Updated 4 years ago
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• mainkoon81 / Study-02-AB-Testing
  Hypothesis testing (Parametric/Non-Parametric)
  ☆11Updated 5 years ago
• Shivanandroy / CategoricalEmbedder
  Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks
  ☆25Updated 5 years ago
• medoidai / ts-changepoint-detection-app
  An R/Shiny app for time-series segmentation and changepoint detection tasks.
  ☆19Updated 5 years ago
• hugopalmer / assortment_optimization
  Source code from my Master's thesis @Polytechnique Montréal. A solution to the assortment optimization problem, able to deal with large n…
  ☆19Updated 8 years ago
• kelvnt / data-drift-detector
  Developmental tools to detect data drift
  ☆16Updated last year
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆51Updated 3 years ago
• sparsh-ai / reco-bandit
  Building recommender Systems using contextual bandit methods to address cold-start issue and online real-time learning
  ☆11Updated 4 years ago
• vub-dl / u-cmab
  Uplifted Contextual Multi-Armed Bandit
  ☆19Updated 3 years ago
• gkamradt / time-series-cheat-sheet
  Quick cheat sheet to time series models using NYC Taxi Data
  ☆16Updated 5 years ago
• theomitsa / python
  ☆7Updated 6 years ago
• leenamurgai / debias-ml
  A practical, explainable and effective method for reducing bias in machine learning algorithms.
  ☆21Updated 5 years ago
• unravelin / code-test-data-science
  Data Scientist code test
  ☆19Updated 5 years ago
• ijmbarr / reducing-variance-ab-tests
  Some notes on techniques for variance reduction to increase the power of A/B tests
  ☆14Updated 6 years ago
• jphall663 / responsible_xai
  Guidelines for the responsible use of explainable AI and machine learning.
  ☆17Updated 2 years ago
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆47Updated 9 months ago
• sachinruk / bayes_school
  ☆16Updated 5 years ago
• deburky / boosting-scorecards
  Boosting scorecards
  ☆14Updated last month
• rozester / LinkedIn-Comments-Analyzer
  Extracting LinkedIn comments from any post and export it to Excel file
  ☆23Updated 6 years ago
• gdmarmerola / cfml_tools
  My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable an…
  ☆31Updated 2 years ago
• ashish-kamboj / Market-Mix-Modeling
  Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
  ☆41Updated 4 years ago
• cbellei / abyes
  A Python package for Bayesian A/B Testing
  ☆61Updated last year
• chiachong / medium-search-app
  A simple search engine to search medium stories built with streamlit and elasticsearch.
  ☆40Updated 3 years ago