h2oai / article-information-2019
Article for Special Edition of Information: Machine Learning with Python
☆13Updated 3 months ago
Alternatives and similar repositories for article-information-2019:
Users that are interested in article-information-2019 are comparing it to the libraries listed below
- H2OAI Driverless AI Code Samples and Tutorials☆37Updated 6 months ago
- Distributed, large-scale, benchmarking framework for rigorous assessment of automatic machine learning repositories, projects, and librar…☆30Updated 2 years ago
- Comparison of automatic machine learning libraries☆27Updated 7 years ago
- Predict whether a student will correctly answer a problem based on past performance using automated feature engineering☆32Updated 4 years ago
- Sample Notebooks for PipelineAI☆44Updated 2 years ago
- Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.☆22Updated 5 years ago
- Brian Farris' Talk on Reinforcement Learning and Multi-Armed Bandits for the Data Incubator☆30Updated 6 years ago
- Exploratory code to see if we can learn about feature relationships in a DataFrame using machine learning☆55Updated 5 years ago
- ☆11Updated 6 years ago
- ☆19Updated 4 years ago
- ☆23Updated last year
- 57th place solution in "Bosch Production Line Performance"☆19Updated 7 years ago
- General Interpretability Package☆58Updated 2 years ago
- Machine Learning Deployment for Kubernetes☆18Updated last year
- Materials for Machine Learning with H2O Open Platform at ODSC Masterclass Summit 2017☆12Updated 8 years ago
- Know your ML Score based on Sculley's paper☆34Updated 6 years ago
- Automated Exploratory Data Analysis. Simplifying Data Exploration☆35Updated 4 years ago
- Using Luigi to create a Machine Learning Pipeline using the Rossman Sales data from Kaggle☆33Updated 8 years ago
- RESTful API hosting xgboost model☆24Updated 7 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆24Updated 7 years ago
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆28Updated 5 years ago
- Kaggle competition results☆20Updated 6 years ago
- Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.☆21Updated 2 years ago
- A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.☆102Updated 3 years ago
- Simple validator for submissions to DrivenData competitions☆19Updated 5 years ago
- How to do data science with Optimus, Spark and Python.☆19Updated 5 years ago
- Notebooks for deep learning course☆14Updated 3 years ago
- Collection of presentation of my work on various platforms and meetups☆22Updated 6 years ago
- Jupyter notebooks for learning Python and Data Science, companion to Data Science Solutions book.☆36Updated 5 years ago
- Python implementation of R package breakDown☆42Updated last year