savarin / rateflask
predicts the rate of return at inception of a Lending Club loan - Mar 2015
☆9Updated 8 years ago
Alternatives and similar repositories for rateflask:
Users that are interested in rateflask are comparing it to the libraries listed below
- Common data science and data engineering utilities to help us perform analytics. Our toolbox for data scientists, licensed under Apache-2…☆30Updated 6 years ago
- Save and load entire workspaces containins pandas objects and numpy arrays☆14Updated 6 years ago
- NumPy and Pandas interface to Big Data☆35Updated last year
- Monotonic Optimal Binning in Consumer Credit Risk Scorecard Development☆60Updated 4 years ago
- Distributed Agent Based On Celery Used To Collect End Of Day Stock Data☆26Updated 7 years ago
- Read better test failures.☆116Updated 7 months ago
- ☆89Updated 6 years ago
- Tutorial session from PyData Washington DC, Fri 7 October 2016☆31Updated 8 years ago
- This repository contains code used for my blog.☆85Updated 7 years ago
- Open Source Tools for Financial Time Series Analysis and Visualization☆69Updated 9 years ago
- Quick informal survey at the Los Angeles Machine learning meetup about tools used for machine learning.☆51Updated 9 years ago
- aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-firs…☆75Updated 8 years ago
- Jupyter Notebook and Python business intelligence tools and techniques. [Raw upload]☆85Updated last year
- ☆74Updated 8 years ago
- ☆34Updated 8 years ago
- ☆45Updated 8 years ago
- Blog system for quant☆39Updated 9 years ago
- An R package for time series models and forecasts with xgboost compatible with {forecast} S3 classes☆140Updated 7 years ago
- Using Facebook's Prophet forecasting library to forecast bitcoin prices☆19Updated 7 years ago
- ☆84Updated 6 years ago
- ⏰ Anomaly Detection with R (separately maintained fork of Twitter's AnomalyDetection 📦)☆91Updated 2 years ago
- A Python API for LendingClub☆101Updated 8 years ago
- Code used to implement various stochastic intensity models for univariate and multivariate credit risk models.