creggian

creggian's Stars

• data-drift/data-drift

  Metrics Observability & Troubleshooting

  Language:HTML31711

• vincentarelbundock/modelsummary

  Beautiful and customizable model summaries in R.

  Language:HTML90975

• kdeldycke/awesome-engineering-team-management

  👔 How to transition from software development to engineering management

  2k144

• mttga/neural_academy_digit_recognition

  Language:Python2

• zhujun98/data-engineering

  Spark, Airflow, Kafka

  Language:Python276

• eficode-academy/git-katas

  A set of exercises for deliberate Git Practice

  Language:Shell1.3k852

• rstudio/vetiver-r

  Version, share, deploy, and monitor models

  Language:R18027

• macmotp/codegen

  Generate human friendly codes

  Language:PHP4

• macmotp/codegen-laravel

  Generate human friendly codes - Laravel extension

  Language:PHP3

• Fraud-Detection-Handbook/fraud-detection-handbook

  Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

  Language:Jupyter Notebook481168

• tidyverts/feasts

  Feature Extraction And Statistics for Time Series

  Language:R29123

• corybrunson/ggalluvial

  ggplot2 extension for alluvial plots

  Language:R49535

• jwasham/coding-interview-university

  A complete computer science study plan to become a software engineer.

  304k76.4k

• MAIF/shapash

  🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

  Language:Jupyter Notebook2.7k331

• sethsandaru/vue-form-builder

  Super Form Builder built on top of Vue with Drag & Drop functionality, savable-form-schema and easy to maintain/upgrade your form.

  Language:Vue413129

• lopusz/awesome-interpretable-machine-learning

  Language:Python902141

• laic-ufmg/Recipe

  Automated machine learning (AutoML) with grammar-based genetic programming

  Language:C5214

• MangoTheCat/python-for-r-users-workshop

  Material for the Python for R Users workshop

  Language:Jupyter Notebook7225

• instillai/machine-learning-course

  :speech_balloon: Machine Learning Course with Python:

  Language:Python7k1.3k

• parrt/random-forest-importances

  Code to compute permutation and drop-column importances in Python scikit-learn models

  Language:Jupyter Notebook597130

• tidyverse/datascience-box

  Data Science Course in a Box

  Language:JavaScript954427

• AutoViML/AutoViz

  Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

  Language:Python1.7k197

• brandon-rhodes/pycon-pandas-tutorial

  PyCon 2015 Pandas tutorial materials

  Language:Jupyter Notebook1k694

• DataTalksClub/awesome-data-podcasts

  A list of awesome data podcasts

  36156

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.2k726

• sirupsen/zk

  Zettelkasten on the command-line 📚 🔍

  Language:Ruby57126

• nf-core/rnaseq

  RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.

  Language:Nextflow864695

• tidymodels/yardstick

  Tidy methods for measuring model performance

  Language:R36754

• huggingface/notebooks

  Notebooks using the Hugging Face libraries 🤗

  Language:Jupyter Notebook3.6k1.5k

• replicate/keepsake

  Version control for machine learning

  Language:Python1.6k72