Bob Green (bgreen-litl)

bgreen-litl

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Company:litl

Location:Boston, MA

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litl

Bob Green's starred repositories

hnswlib

Header-only C++/python library for fast approximate nearest neighbors

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docarray

Represent, send, store and search multimodal data

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zarr-python

An implementation of chunked, compressed, N-dimensional arrays for Python.

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developer

the first library to let you embed a developer agent in your own app!

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miniforge

A conda-forge distribution.

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feast

The Open Source Feature Store for Machine Learning

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hass-weatherflow

Home Assistant Integration for WeatherFlow Stations

Language:PythonLicense:MITStargazers:70Issues:0Issues:0

patito

A data modelling layer built on top of polars and pydantic

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pytest-memray

pytest plugin for easy integration of memray memory profiler

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scalene

Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals

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pottery

Redis for humans. 🌎🌍🌏

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memray

Memray is a memory profiler for Python

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pandera

A light-weight, flexible, and expressive statistical data testing library

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arq

Fast job queuing and RPC in python with asyncio and redis.

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holoviews

With Holoviews, your data visualizes itself.

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sqlmodel

SQL databases in Python, designed for simplicity, compatibility, and robustness.

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uvicorn

An ASGI web server, for Python. 🦄

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mamba

The Fast Cross-Platform Package Manager

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hysds

Hybrid Cloud Science Data System Framework

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fx

Terminal JSON viewer & processor

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pip

The Python package installer

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invoke

Pythonic task management & command execution.

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flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

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werkzeug

The comprehensive WSGI web application library.

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backoff

Python library providing function decorators for configurable backoff and retry

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bert

TensorFlow code and pre-trained models for BERT

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BERT-keras

Keras implementation of BERT with pre-trained weights

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faiss

A library for efficient similarity search and clustering of dense vectors.

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cpython

The Python programming language

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dynet_tutorial_examples

Tutorial on "Practical Neural Networks for NLP: From Theory to Code" at EMNLP 2016

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