ing-bank / industry2vecLinks
☆29Updated 6 years ago
Alternatives and similar repositories for industry2vec
Users that are interested in industry2vec are comparing it to the libraries listed below
Sorting:
- vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distr…☆121Updated 9 months ago
- Buy Till You Die and Customer Lifetime Value statistical models in Python.☆117Updated last year
- Data Scientist code test☆19Updated 5 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 3 years ago
- ☆26Updated 7 years ago
- ☆39Updated 5 months ago
- Hierarchical Time Series Forecasting using Prophet☆144Updated 4 years ago
- In which I play with the ideas surrounding causality☆53Updated 3 years ago
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 4 years ago
- Work-In-Progress: conjoint analysis in Python☆51Updated 7 years ago
- Python package for Bayesian Tests / AB Testing☆39Updated 5 years ago
- Python implementation of R package breakDown☆43Updated 2 years ago
- Distributed Bayesian Entity Resolution in Apache Spark☆57Updated 4 years ago
- Public repo for the pymetalog project☆39Updated 3 years ago
- ☆97Updated 7 years ago
- Abstractions for feature engineering on large graphs of tabular data.☆22Updated 2 weeks ago
- A list of resources for current and aspiring data science managers☆16Updated 4 years ago
- CBM Encoding☆19Updated 4 years ago
- Visualization ideas for data science☆20Updated 7 years ago
- Performance of various open source GBM implementations☆222Updated last year
- Forecasting Uber demand in NYC neighborhoods☆34Updated 7 years ago
- An extension of CatBoost to probabilistic modelling☆147Updated last year
- Tutorial on multilevel modeling, using Gelman radon example☆58Updated 10 years ago
- Predict whether a student will correctly answer a problem based on past performance using automated feature engineering☆32Updated 5 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success