riemann85

keras

Deep Learning for humans

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

evidently

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

gluonts

Probabilistic time series modeling in Python

sparrow

Data processing with ML and LLM

modAL

A modular active learning framework for Python

stat-learning

Notes and exercise attempts for "An Introduction to Statistical Learning"

CNN_sentence

CNNs for sentence classification

sent2vec

General purpose unsupervised sentence representations

skrub

Prepping tables for machine learning

cdQA

⛔ [NOT MAINTAINED] An End-To-End Closed Domain Question Answering System.

mmm_stan

Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

pystacknet

LightGBM-with-Focal-Loss

An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems

kuma_utils

My toolbox for data analysis. :)

gauss-rank-scaler

Scikit-learn compatible implementation of the Gauss Rank scaling method

vincent

cdQA-ui

⛔ [NOT MAINTAINED] A web interface for cdQA and other question answering systems.

bayes_course_dec_2023

Probabilistic Programming and Bayesian Computing with PyMC

EMJMCMC2016

Bayesian model configuration, selection and averaging in complex regression contexts

target-likelihood-encoding

Generate target statistics

predictor_stacker

Linear Predictor Stacker aims at optimizing predictor's weights against a ML metric

MulDIC

MulDIC: A Multimodal Deep Learning Model using Text, Image, and Code Data for Improving Issue Classification Tasks

hyperbolic-image-embeddings

Supplementary code for the paper "Hyperbolic Image Embeddings".

pycal

Python implementation of functional data analysis methods applied to calibration of numerical models with functional response

AIX360

Interpretability and explainability of data and machine learning models