PacktPublishing / Applied-Machine-Learning-Explainability-Techniques
Applied Machine Learning Explainability Techniques, published by Packt
☆237Updated last year
Related projects ⓘ
Alternatives and complementary repositories for Applied-Machine-Learning-Explainability-Techniques
- Practical Deep Learning at Scale with MLFlow, published by Packt☆159Updated 11 months ago
- Machine Learning for Streaming Data with Python, published by Packt☆68Updated last year
- Comet for Data Science, published by Packt☆42Updated last year
- ☆146Updated 2 years ago
- Code repository for the online course Hyperparameter Optimization for Machine Learning☆111Updated last month
- Demo for CI/CD in a machine learning project☆93Updated last year
- A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.☆165Updated 2 months ago
- An end-to-end project on customer segmentation☆82Updated last year
- Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt☆190Updated last year
- Slides for "Feature engineering for time series forecasting" talk☆57Updated 2 years ago
- Code Repository for The Kaggle Workbook, Published by Packt☆113Updated last year
- Code repository for the online course "Feature Engineering for Time Series Forecasting".☆173Updated 11 months ago
- The repository contains a list of projects which I will work on while learning and implementing MLOps.☆79Updated last year
- A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)☆71Updated last year
- References to the Medium articles☆86Updated 2 years ago
- Interpretable Machine Learning with Python, published by Packt☆446Updated last year
- Code repository for the online course Machine Learning with Imbalanced Data☆161Updated 2 months ago
- I will share about Machine Learning and Deep Learning.☆111Updated last year
- Python Feature Engineering Cookbook, published by Packt☆461Updated last year
- Explainable AI with Python, published by Packt☆156Updated last year
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆88Updated 10 months ago
- Code repository for the book feature selection in machine learning☆24Updated this week
- Machine Learning for Imbalanced Data, published by Packt☆261Updated 6 months ago
- Example machine learning pipeline with MLflow and Hydra☆87Updated last year
- Machine Learning Engineering with Python☆171Updated last year
- Kaggle Pipeline for tabular data competitions☆204Updated 4 months ago
- Reference code base for ML Engineering, Manning Publications☆122Updated 3 years ago
- Engineering MLOps, published by Packt☆177Updated last year
- ☆110Updated 8 months ago
- A set of examples illustrating some possible use cases for NannyML☆19Updated last year