yuanli1's repositories
airflow-backfill-util
Airflow Backfill UI based plugin for existing / new Airflow environment
airflow-on-kubernetes
A guide to running Airflow on Kubernetes
ASTRA
Self-training with Weak Supervision (NAACL 2021)
astronomer
Helm Charts for the Astronomer Platform, Apache Airflow as a Service on Kubernetes
Awesome-Weak-Supervision
A curated list of programmatic weak supervision papers and resources
datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
faker
Faker is a Python package that generates fake data for you.
fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
FastChat
The release repo for "Vicuna: An Open Chatbot Impressing GPT-4"
fucking-algorithm
刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.
gpt4all
gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue
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.
holoclean
A Machine Learning System for Data Enrichment.
interpret
Fit interpretable models. Explain blackbox machine learning.
ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
mlx
MLX: An array framework for Apple silicon
netron
Visualizer for neural network, deep learning, and machine learning models
papermill
📚 Parameterize, execute, and analyze notebooks
presto-on-k8s
Setup for running Presto with Hive Metastore on Kubernetes
pygooglenews
If Google News had a Python library
python-deequ
Python API for Deequ
qlora
QLoRA: Efficient Finetuning of Quantized LLMs
superset
Apache Superset is a Data Visualization and Data Exploration Platform
superset-api-client
A Python Client for Apache Superset REST API
the-algorithm
Source code for Twitter's Recommendation Algorithm
Weakly_Supervised_Learning
Weakly Supervised Learning: Introduction and Best Practices