githubbabrova

githubbabrova's Stars

• google/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30k3285.5k2.7k

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.9k2442.5k3.3k

• openai/gpt-2

  Code for the paper "Language Models are Unsupervised Multitask Learners"

  Language:Python22.5k6342665.5k

• HumanSignal/label-studio

  Label Studio is a multi-type data labeling and annotation tool with standardized output format

  Language:JavaScript19.3k1782.3k2.4k

• ramitsurana/awesome-kubernetes

  A curated list for awesome kubernetes sources :ship::tada:

  Language:Shell15.1k4602382.3k

• horovod/horovod

  Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

  Language:Python14.3k3352.2k2.2k

• great-expectations/great_expectations

  Always know what to expect from your data.

  Language:Python10k821.9k1.5k

• awsdocs/aws-doc-sdk-examples

  Welcome to the AWS Code Examples Repository. This repo contains code examples used in the AWS documentation, AWS SDK Developer Guides, and more. For more information, see the Readme.md file below.

  Language:Java9.6k2022.3k5.6k

• activeloopai/deeplake

  Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

  Language:Python8.2k90465625

• PAIR-code/facets

  Visualizations for machine learning datasets

  Language:Jupyter Notebook7.4k268159886

• Kaggle/kaggle-api

  Official Kaggle API

  Language:Python6.3k2004861.1k

• snorkel-team/snorkel

  A system for quickly generating training data with weak supervision

  Language:Python5.8k166980857

• airbnb/aerosolve

  A machine learning package built for humans.

  Language:Scala4.8k35219564

• man-group/dtale

  Visualizer for pandas data structures

  Language:TypeScript4.8k75590406

• chiphuyen/ml-interviews-book

  https://huyenchip.com/ml-interviews-book/

  Language:HTML3.4k4614523

• SkalskiP/make-sense

  Free to use online tool for labelling photos. https://makesense.ai

  Language:TypeScript3.2k54193525

• GokuMohandas/mlops-course

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook3k5519517

• modAL-python/modAL

  A modular active learning framework for Python

  Language:Python2.2k44147324

• pyscaffold/pyscaffold

  🛠 Python project template generator with batteries included

  Language:Python2.1k39297183

• RafeKettler/magicmethods

  Guide to Python's magic methods

  Language:HTML1.7k7848347

• nsacyber/WALKOFF

  A flexible, easy to use, automation framework allowing users to integrate their capabilities and devices to cut through the repetitive, tedious tasks slowing them down. #nsacyber

  Language:Python1.2k90136222

• karpathy/arxiv-sanity-lite

  arxiv-sanity lite: tag arxiv papers of interest get recommendations of similar papers in a nice UI using SVMs over tfidf feature vectors based on paper abstracts.

  Language:Python1.2k228132

• 8080labs/ppscore

  Predictive Power Score (PPS) in Python

  Language:Python1.1k2762167

• NUAA-AL/ALiPy

  ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

  Language:Python8692834115

• trent-b/iterative-stratification

  scikit-learn cross validators for iterative stratification of multilabel data

  Language:Python85262775

• ntucllab/libact

  Pool-based active learning in Python

  Language:Python77859100174

• tensorflow/data-validation

  Library for exploring and validating machine learning data

  Language:Python76549169174

• firmai/deltapy

  DeltaPy - Tabular Data Augmentation (by @firmai)

  Language:Jupyter Notebook53617353

• quil-lang/qvm

  The high-performance and featureful Quil simulator.

  Language:Common Lisp4152513657

• mit-pdos/xv6-book

  Commentary for xv6-public

  Language:Perl24840865