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ag-release-tools

autogluon

AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data

autogluon-cloud

Autogluon-cloud aims to provide user tools to train, fine-tune and deploy AutoGluon backed models on the cloud. With just a few lines of codes, users could train a model and perform inference on the cloud without worrying about MLOps details such as resource management

autogluon-team-utils

autogluon.common-feedstock

A conda-smithy repository for autogluon.common.

autogluon.multimodal-feedstock

A conda-smithy repository for autogluon.multimodal.

automm-benchmark-paper

OpenML AutoMM Benchmarking Scripts

automm_bugbash

chatbot

ci-test

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.

docker-autogluon

gluonts-feedstock

A conda-smithy repository for gluonts.

howto-weaviate-retrieval-plugin

langchain

⚡ Building applications with LLMs through composability ⚡

ml-000

mlops-e2e

MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK

mm-cot

Official implementation for "Multimodal Chain-of-Thought Reasoning in Language Models" (stay tuned and more will be updated)

plugins-qs

python-high-performance-second-edition

Python High Performance – Second Edition, published by Packt

sagemaker-distribution

A set of Docker images that include popular frameworks for machine learning, data science and visualization.

sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker

scipy_con_2019

Tutorial Sessions for SciPy Con 2019

shellkoans

timeseriesanalysiswithpython

vertex-ai-samples

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud