writeAheadLog

writeAheadLog's Stars

• ohmyzsh/ohmyzsh

  🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python, etc), 140+ themes to spice up your morning, and an auto-update tool that makes it easy to keep up with the latest updates from the community.

  Language:Shell175k2.6k4.9k26k

• ollama/ollama

  Get up and running with Llama 3.3, Phi 4, Gemma 2, and other large language models.

  Language:Go107k6155.4k8.5k

• keras-team/keras

  Deep Learning for humans

  Language:Python62.3k1.9k12.3k19.5k

• scikit-learn/scikit-learn

  scikit-learn: machine learning in Python

  Language:Python60.7k2.1k11.3k25.5k

• romkatv/powerlevel10k

  A Zsh theme

  Language:Shell47.3k1872.5k2.2k

• isocpp/CppCoreGuidelines

  The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

  Language:CSS43.1k2k1.2k5.5k

• apache/spark

  Apache Spark - A unified analytics engine for large-scale data processing

  Language:Scala40.3k2k028.4k

• apache/airflow

  Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

  Language:Python38.2k76610.4k14.5k

• ageron/handson-ml2

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook28.2k65751212.8k

• ageron/handson-ml

  ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

  Language:Jupyter Notebook25.3k1.1k56212.9k

• zsh-users/zsh-syntax-highlighting

  Fish shell like syntax highlighting for Zsh.

  Language:Shell20.5k1366971.3k

• mlflow/mlflow

  Open source platform for the machine learning lifecycle

  Language:Python19.2k3064k4.3k

• Netflix/metaflow

  Open Source AI/ML Platform

  Language:Python8.4k292669781

• amueller/introduction_to_ml_with_python

  Notebooks and code for the book "Introduction to Machine Learning with Python"

  Language:Jupyter Notebook7.5k3701494.6k

• aws-samples/aws-cdk-examples

  Example projects using the AWS CDK

  Language:Python5.2k803452.2k

• hunkim/DeepLearningZeroToAll

  TensorFlow Basic Tutorial Labs

  Language:Jupyter Notebook4.5k422752.7k

• mercari/ml-system-design-pattern

  System design patterns for machine learning

  2.4k7414255

• Team-Neighborhood/I-want-to-study-Data-Science

  데이터 사이언스를 공부하고 싶은 분들을 위한 글

  1.8k993484

• aws-samples/aws-glue-samples

  AWS Glue code samples

  Language:Python1.5k7587824

• msbaek/clean-coders-2013

  2013년 7~9월 클린 코더스 강의

  31215083

• aws-samples/mlops-amazon-sagemaker

  Workshop content for applying DevOps practices to Machine Learning workloads using Amazon SageMaker

  Language:Jupyter Notebook304157125

• aws-samples/aws-ai-ml-workshop-kr

  A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.

  Language:Jupyter Notebook255196144

• Netflix/metaflow-service

  :rocket: Metadata tracking and UI service for Metaflow!

  Language:Python1961915071

• gyuwon/TDDHandsOn

  Fast campus 강의 '현실 세상의 TDD' 실습에 사용된 예제 코드를 제공합니다.

  Language:Java18412255

• aws/sagemaker-scikit-learn-container

  Support code for building and running Amazon SageMaker compatible Docker containers based on the open source framework Scikit-learn (http://scikit-learn.org/stable/)

  Language:Python1744649109

• aws/sagemaker-xgboost-container

  This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.

  Language:Python12929080

• aws-samples/amazon-sagemaker-mlops-workshop

  MLOps workshop with Amazon SageMaker

  Language:Jupyter Notebook937425

• aws-samples/mlops-sagemaker-github-actions

  MLOps example using Amazon SageMaker Pipeline and GitHub Actions

  Language:Python695545

• feast-dev/feast-gcp-fraud-tutorial

  Resources backing the Feast fraud tutorial on GCP

  Language:Jupyter Notebook132014

• moseskim/ml-at-work

  머신러닝 실무 프로젝트 (2판) 샘플 코드 저장소입니다.

  Language:Jupyter Notebook8105