buyuknacar's Stars
microsoft/playwright-python
Python version of the Playwright testing and automation library.
PauloGoncalvesBH/running-playwright-on-aws-lambda
Running hundreds of Playwright E2E tests in a few seconds with AWS Lambda
umihico/docker-selenium-lambda
The simplest demo of chrome automation by python and selenium in AWS Lambda
alex9smith/gdelt-doc-api
A Python client for the GDELT 2.0 Doc API
open-guides/og-aws
📙 Amazon Web Services — a practical guide
michaelfedell/docker-for-ml-tutorial
fchollet/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
frankelavsky/intro_to_web_workshop
Introduction to Web Technology Workshop by Frank Elavsky
tatsu-lab/stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
nuitrcs/Julia_workshop
Materials for Julia language workshop
NUMLDS/2024-400-group6
ray-project/llm-applications
A comprehensive guide to building RAG-based LLM applications for production.
michaelfedell/linux_essentials
A collection of basic information and practical tools for working in a linux environment. Prepared for Northwestern MSiA.
NUMLDS/bootcamp-2023
lbdeoliveira/song-playlist-recommendation
This project was a joint effort by Lucas De Oliveira, Chandrish Ambati, and Anish Mukherjee to create a song and playlist embeddings for recommendations in a distributed fashion using a 1M playlist dataset by Spotify.
karpathy/llama2.c
Inference Llama 2 in one file of pure C
cgpotts/cs224u
Code for Stanford CS224u
joonspk-research/generative_agents
Generative Agents: Interactive Simulacra of Human Behavior
Lightning-AI/litgpt
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
google/sentencepiece
Unsupervised text tokenizer for Neural Network-based text generation.
yuchenlin/LLM-Blender
[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.
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.
kennethleungty/AWS-Certified-Cloud-Practitioner-Notes
Notes compiled based on AWS E-Learning lessons and transcripts