newgrit1004's starred repositories

pytorch-benchmark

Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption

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Lora-for-Diffusers

The most easy-to-understand tutorial for using LoRA (Low-Rank Adaptation) within diffusers framework for AI Generation Researchers🔥

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tutorials

This repository contains tutorials and examples for Triton Inference Server

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mnist-fastapi-aio-triton

Simple example of FastAPI + gRPC AsyncIO + Triton

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algorithmic-efficiency

MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

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tech-jobs-with-relocation

All-in-one guide to getting a tech job abroad 🌎

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machine-learning-interview

Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.

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mindsdb

The platform for building AI from enterprise data

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tips

Most commonly used git tips and tricks.

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ml-system-design-pattern

System design patterns for machine learning

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system-design-primer

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

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rust-companies

A list of companies using Rust in production.

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rust-mlops-template

A work in progress to build out solutions in Rust for MLOPs

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baekjoon

코딩테스트 대비 문제집(Baekjoon Online Judge)

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milewski-ctfp-pdf

Bartosz Milewski's 'Category Theory for Programmers' unofficial PDF and LaTeX source

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whisper_real_time

Real time transcription with OpenAI Whisper.

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Dataloader-Optimization

Getting GPU Util 99%

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yt-dlp

A feature-rich command-line audio/video downloader

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deep_learning_study

A curated list of Deep Learning

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goQuality-dev-contents

{ 고퀄리티 :zap: 개발 컨텐츠 모음 }

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PythonCheatSheet

A Cheat Sheet 📜 to revise Python syntax. Particularly useful for solving Data Structure and Algorithmic problems with Python.

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recoteam

카카오 추천팀 공개 리포지토리입니다.

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recommenders

Best Practices on Recommendation Systems

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cinnamon

CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system

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ml-design-patterns

O'Reilly <머신러닝 디자인 패턴 Machine Learning Design Patterns> 소스코드 저장소

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ml-design-patterns

Source code accompanying O'Reilly book: Machine Learning Design Patterns

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jax-models

Unofficial JAX implementations of deep learning research papers

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AB-Testing

A/B Testing — A complete guide to statistical testing

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