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21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
10 Weeks, 20 Lessons, Data Science for All!
The fastai book, published as Jupyter Notebooks
An open-source, low-code machine learning library in Python
Automatic extraction of relevant features from time series:
Book about interpretable machine learning
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Repository containing notebooks of my posts on Medium
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Welcome to the Physics-based Deep Learning Book (v0.2)
Lightweight, useful implementation of conformal prediction on real data.
Course materials for: Geospatial Data Science
Writing clean and optimized Python code
Parallel Hyperparameter Tuning in Python
A python library to build Model Trees with Linear Models at the leaves.
Numenta published papers code and data
Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
A collection of non-residential buildings for performance analysis and algorithm benchmarking
A python package for time series forecasting with scikit-learn estimators.
Repository for machine learning and remote sensing pipeline described in Kruitwagen, L., Story, K., Friedrich, J, et. al. (2019) , used to produce a global inventory of utility-scale solar photvolt…
A set of tools for processing of spatial and temporal disaggregations.
Dash web app showing when an engine is expected to fail powered by vaex and tf/keras.
A Python library for Bayesian Anomaly Detection
Jupyter notebook tutorials about fundamental machine learning algorithms
A very simple (and probably useless) bus prediction service. Final project for MLOps Zoomcamp course, 2022 edition.
Webapp for exploring Data outside