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Search results for ml pipeline
406 search results found
🔮 Build multimodal AI services via cloud native technologies
Machine Learning Toolkit for Kubernetes
A Python framework for creating maintainable and modular data science code.
Official Stanford NLP Python Library for Many Human Languages
Image augmentation library in Python for machine learning.
🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data.
ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
Build data pipelines, the easy way 🛠️
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Production Level Deep Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
Machine Learning Pipelines for Kubeflow
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
Machine learning platform for Web developers
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
TFX is an end-to-end platform for deploying production ML pipelines
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
Provide an input CSV and a target field to predict, generate a model + code to run it.
Elyra extends JupyterLab with an AI centric approach.
A Julia machine learning framework
Data Science Complete Tutorial
For extensive instructor led learning
MLBox is a powerful Automated Machine Learning python library.
PyTorch extensions for fast R&D prototyping and Kaggle farming
Finding the genre of a song with Deep Learning
Machine Learning automation and tracking
Nlp With Ruby
Curated List: Practical Natural Language Processing done in Ruby
TODS: An Automated Time-series Outlier Detection System
An open-source ML pipeline development platform
【A simple C++ DAG framework】 一个简单好用的、无任何三方依赖的、跨平台的、收录于awesome-cpp的、基于流图的并行计算框架。 & fork
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
LAMA - automatic model creation framework
💥 Use the latest Stanza (StanfordNLP) research models directly in spaCy
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
EvalML is an AutoML library written in python.
Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
A graph-based functional API for building complex scikit-learn pipelines.
A one-stop repository for low-code easily-installable object detection pipelines.
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Kubeflow’s superfood for Data Scientists
Pythonic tool for running machine-learning/high performance/quantum-computing workflows in heterogenous environments.
Open Solution Home Credit
Open solution to the Home Credit Default Risk challenge 🏡
Aspect Based Sentiment Analysis
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
Model Card Toolkit
A toolkit that streamlines and automates the generation of model cards
ML pipeline orchestration and model deployments on Kubernetes, made really easy.
Get protein embeddings from protein sequences
Open Solution Mapping Challenge
Open solution to the Mapping Challenge 🌎
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
SynthDet - An end-to-end object detection pipeline using synthetic data
Automated Payload Reverse Engineering Pipeline for the Controller Area Network (CAN) protocol
NLP Capabilities in Neo4j
Simple and flexible ML workflow engine
Cookiecutter template for FastAPI projects using: Machine Learning, Poetry, Github Actions and Pytests
Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning Pipeline.
Python machine learning package providing simple interoperability between ML.NET and scikit-learn components.
Java library and command-line application for converting Apache Spark ML pipelines to PMML
An end-to-end machine learning and data mining framework on Hadoop
Morphl Community Edition
MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization
Forte is a flexible and powerful ML workflow builder. This is part of the CASL project: http://casl-project.ai/
TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.
An ML framework to accelerate research and its path to production.
PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
Toloka-Kit is a Python library for working with Toloka API.
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.
Profile and monitor your ML data pipeline end-to-end
Developer platform for production ML.
A simple Spark-powered ETL framework that just works 🍺
Feature Selection For Machine Learning
Code repository for the online course Feature Selection for Machine Learning
Open Solution Toxic Comments
Open solution to the Toxic Comment Classification Challenge
Sweet data-centric foundation model fine-tuning
A simple guide to MLOps through ZenML and its various integrations.
😄 Dataset for Emotion Classification
Lightweight, Python library for fast and reproducible experimentation 🔬
Machine Learning eXchange (MLX). Data and AI Assets Catalog and Execution Engine
🏭 PDF text extraction pipeline: self-hosted, local-first, Docker-based
Automated Tool for Optimized Modelling
Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.
A fast image augmentation library in Julia for machine learning.
Dataflow Programming for Machine Learning in R
Open Solution Salt Identification
Open solution to the TGS Salt Identification Challenge
Automatic Speech Recognition
🎧 Automatic Speech Recognition: DeepSpeech & Seq2Seq (TensorFlow)
A library for composing end-to-end tunable machine learning pipelines.
Spark Nlp Models
Models and Pipelines for the Spark NLP library
Build and deploy a serverless data pipeline on AWS with no effort.
K3ai is a lightweight, fully automated, AI infrastructure-in-a-box solution that allows anyone to experiment quickly with Kubeflow pipelines. K3ai is perfect for anything from Edge to laptops.
Python library for converting Apache Spark ML pipelines to PMML
AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
An automatic engine for predicting materials properties.
Deploy DL/ ML inference pipelines with minimal extra code.
Transforms and pipelines with tabular data in Julia
Pycrop Yield Prediction
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
Service for quick deploying and using dockerized Computer Vision models
End to end MLRun demos
MLeap allows for easily putting Spark ML pipelines into production
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