tuliocasagrande

black

The uncompromising Python code formatter

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

faiss

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

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

memray

Memray is a memory profiler for Python

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

optuna

A hyperparameter optimization framework

BentoML

The easiest way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Multi-model Inference Graph/Pipelines, LLM/RAG apps, and more!

aws-serverless-workshops

Code and walkthrough labs to set up serverless applications for Wild Rydes workshops

spark-nlp

State of the Art Natural Language Processing

smart_open

Utils for streaming large files (S3, HDFS, gzip, bz2...)

m2cgen

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

mit-15-003-data-science-tools

Study guides for MIT's 15.003 Data Science Tools

data

A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.

nbQA

Run ruff, isort, pyupgrade, mypy, pylint, flake8, and more on Jupyter Notebooks

deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

tueplots

Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other scientific publications.

sagemaker-ssh-helper

A helper library to connect into Amazon SageMaker with AWS Systems Manager and SSH (Secure Shell)

spellchecker

Spellchecker for JupyterLab notebook markdown cells and file editor.

tensorflow-lifetime-value

Predict customer lifetime value using AutoML Tables, or ML Engine with a TensorFlow neural network and the Lifetimes Python library.

sagemaker-scikit-learn-container

Support code for building and running Amazon SageMaker compatible Docker containers based on the open source framework Scikit-learn (http://scikit-learn.org/stable/)

sagemaker-debugger

Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors

sagemaker-studio-auto-shutdown-extension

amazon-sagemaker-build-train-deploy

Scale complete ML development with Amazon SageMaker Studio

Content-AWS-Certified-Data-Analytics---Speciality

DAS-C01 ACG/LA by Brock Tubre and John Hanna

sagemaker-xgboost-container

This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.

aws-customer-churn-pipeline

An End to End Customer Churn Prediction solution using AWS services.

PyTorchTutorials

PyTorch Tutorial materials for Duke University +Data Science Initiative

amazon-mlops-example-tensorflow

Builds and deploys a MLOps Pipeline on AWS Cloud

terraform-workshop