ML Ops

Explore 798 open source projects in ML Ops

Showing 61-80 of 798 projects

DLR-RM/stable-baselines3

Reliable PyTorch implementations of reinforcement learning algorithms for AI and robotics applications.

12.8K
Active
Python
ML Ops
PyTorch
#reinforcement-learning#robotics#machine-learning

tensorflow/playground

An interactive playground for exploring and experimenting with neural networks in the browser.

12.8K
Active
TypeScript
ML Ops
React
#neural-networks#machine-learning#visualization

DataTalksClub/machine-learning-zoomcamp

This is a free 4-month course to learn machine learning engineering, covering deployment, Docker, FastAPI, and more.

12.7K
Stable
Jupyter Notebook
ML Ops
FastAPI
#machine-learning#deployment#docker

apache/predictionio

PredictionIO is a machine learning server for developers and ML engineers, enabling building and deploying production-ready ML services.

12.5K
Archived
Scala
ML Ops
Scala
#big-data#machine-learning#predictive-analytics

apple/turicreate

A powerful library that simplifies the development of custom machine learning models using Python.

11.2K
Archived
C++
ML Ops
Python
#machine-learning#deep-learning#python

rushter/MLAlgorithms

A collection of minimal and clean examples of machine learning algorithm implementations in Python.

11.0K
Experimental
Python
ML Ops
Python
#machine-learning#deep-learning#neural-networks

numba/numba

NumPy-aware dynamic Python compiler using LLVM, enabling fast, high-performance array and numerical computing.

10.9K
Active
Python
ML Ops
NumPy
#compiler#cuda#llvm

aws/amazon-sagemaker-examples

A collection of Jupyter notebooks showcasing how to build and deploy machine learning models with Amazon SageMaker.

10.9K
Active
Jupyter Notebook
ML Ops
Jupyter Notebook
#machine-learning#deep-learning#data-science

wandb/wandb

The AI developer platform to train and fine-tune models, and manage models from experimentation to production.

10.9K
Active
Python
ML Ops
PyTorch
#ai#machine-learning#model-versioning

cupy/cupy

A GPU-accelerated NumPy & SciPy library for high-performance scientific computing

10.8K
Active
Python
ML Ops
Python
#cuda#gpu#numpy

Jack-Cherish/Machine-Learning

Open-source machine learning library in Python with implementations of popular algorithms like kNN, decision trees, and SVM.

10.2K
Archived
Python
ML Ops
Python
#machine-learning#python#algorithms

autogluon/autogluon

Fast and accurate machine learning framework that can build models in just 3 lines of Python code.

10.1K
Active
Python
ML Ops
PyTorch
#automated-machine-learning#computer-vision#tabular-data

xlite-dev/LeetCUDA

LeetCUDA is a comprehensive collection of modern CUDA learning resources, including 200+ CUDA kernels, Tensor Cores, HGEMM, and FA-2 MMA.

9.8K
Active
Cuda
ML Ops
PyTorch
#cuda#cuda-toolkit#cuda-demo

facebookresearch/demucs

An open-source library for hybrid spectrogram and waveform source separation, useful for audio processing tasks.

9.8K
Archived
Python
ML Ops
Python
#audio-processing#source-separation#machine-learning

tflearn/tflearn

A high-level deep learning library for TensorFlow, enabling developers to build complex neural networks with ease.

9.6K
Archived
Python
ML Ops
TensorFlow
#deep-learning#machine-learning#neural-network

skypilot-org/skypilot

Easily run, manage, and scale AI workloads on any infrastructure using a unified platform.

9.5K
Active
Python
ML Ops
Python
#cloud-computing#cloud-management#cost-optimization

onnx/models

A collection of pre-trained, state-of-the-art AI models in the ONNX format for developers to use in their projects.

9.5K
Stable
Jupyter Notebook
ML Ops
Jupyter Notebook
#deep-learning#models#onnx

sjwhitworth/golearn

golearn is a Go library for machine learning, providing a simple and extensible API for building ML models.

9.4K
Archived
Go
ML Ops
#machine-learning#go#api

arogozhnikov/einops

A flexible and powerful tensor operations library for readable and reliable deep learning code in Python.

9.4K
Active
Python
ML Ops
PyTorch
#deep-learning#tensor-operations#numpy

Oneflow-Inc/oneflow

OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

9.4K
Stable
C++
ML Ops
C++
#deep-learning#cuda#distributed
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