conorosully / SHAP-tutorial
SHAP with Python
☆41Updated last month
Related projects ⓘ
Alternatives and complementary repositories for SHAP-tutorial
- Code used to obtain results for my medium articles☆70Updated last year
- Tackling Climate Change with Time Series Analysis and Forecasting☆31Updated last year
- Modern Time Series Forecasting with Python 2E, Published by Packt☆47Updated last week
- Notebook to accompany MSTL article☆37Updated 2 years ago
- How to Interpret SHAP Analyses: A Non-Technical Guide☆45Updated 3 years ago
- Forecasting: Principles and Practice☆30Updated 3 years ago
- ☆19Updated 7 months ago
- Time Series Analysis and Forecasting in Python☆117Updated 3 months ago
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…☆60Updated 3 weeks ago
- This repository contains the codes for the Python tutorials on statology.org☆24Updated 3 years ago
- ☆19Updated 3 years ago
- Code repository for "Modern Statistics: A Computer Based Approach with Python" and "Industrial Statistics: A Computer Based Approach with…☆87Updated 3 months ago
- Python tutorial on machine learning with time series for DSSGx 2020☆23Updated 4 years ago
- A python library to automate feature selection process for machine learning projects.☆49Updated last year
- Interpretable ML with Python, 2E - published by Packt☆83Updated 7 months ago
- ☆13Updated last year
- Examples of the application of individual scalecast models☆46Updated last year
- Code repository for the course "Forecasting with Machine Learning Models"☆16Updated 5 months ago
- Python notebooks for the tutorial paper on feature selection☆27Updated last year
- This repository holds my paper implementations made for my studies and my content production☆33Updated 3 weeks ago
- Explore how Natural Language Processing (NLP) can be used to assist in identifying and mapping climate-relevant literature using a superv…☆36Updated 3 months ago
- Content from the University of British Columbia's Master of Data Science course DSCI 572.☆37Updated 3 years ago
- The goal of this notebook is to implement and compare different approaches to predict item-level sales at different store locations.☆34Updated 2 years ago
- Using Machine Learning and R to Forecast Wind Energy in the California Power Grid ⚡💨📈☆10Updated 7 months ago
- A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)☆70Updated last year
- Principal Component Regression - Clearly Explained and Implemented☆11Updated 2 years ago
- Ensemble wavelet based neural network for generating epidemiological forecasting (epicasting)☆14Updated 3 months ago
- Machine learning models applied to water demand forecasting in the City of London.☆50Updated 3 weeks ago
- ☆11Updated 5 months ago
- Exploratory Spatial Data Analysis with Python☆25Updated 4 years ago