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171 search results found

MLeap allows for easily putting Spark ML pipelines into production

Understaing Datasets Estimators Tfrecords ⭐ 75

Try to use tf.estimator and tf.data together to train a cnn model.

Monai Deploy App Sdk ⭐ 74

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

Multilingual Latent Dirichlet Allocation Lda ⭐ 73

A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.

Niffler: A DICOM Framework for Machine Learning and Processing Pipelines.

🦅Hyperparameter optimization for machine learning pipelines 🦅

Prism is the easiest way to develop, orchestrate, and execute data pipelines in Python.

Mlprimitives ⭐ 67

Primitives for machine learning and data science.

Person_following_bot ⭐ 65

This is a deep learning based robot which follows a person in dynamic environment.

Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many design choices.

Gunpowder ⭐ 62

A library to facilitate machine learning on multi-dimensional images.

Pipeliner ⭐ 61

Machine learning pipelines for R.

Examples ⭐ 60

📝 Examples of how to use Neptune for different use cases and with various MLOps tools

Home Credit Default Risk ⭐ 59

Default risk prediction for Home Credit competition - Fast, scalable and maintainable SQL-based feature engineering pipeline

Oreilly Ai K8s Tutorial ⭐ 58

Materials for the "AI on Kubernetes" tutorial at O'Reilly AI SF 2018

Mlinspect ⭐ 57

Inspect ML Pipelines in Python in the form of a DAG

Aireferencearchitectures ⭐ 56

Official Azure Reference Architectures for AI workloads

Frontend Regression Validator ⭐ 55

Visual regression tool used to compare baseline and updated instances of a website in a deployment pipeline.

Cherry On Py ⭐ 53

Cloud computing is a game changer for developers. What can you do in a couple hundred lines of code?

Pravda Ml ⭐ 52

This project is used to capture machine learning pipelines created on top of Spark as OK

Elk_twitter ⭐ 52

This is a data pipeline for Twitter (ETL) using the elastic stack Elasticsearch, Logstash and Kibana (version 6.1)

Twde Datalab ⭐ 52

Onboarding to data science by ThoughtWorks

Chemometricstools.jl ⭐ 51

A collection of tools for chemometrics and machine learning written in Julia.

nPrint provides a generalizable data representation for network packets that works directly with machine learning techniques

Pythonframeworks ⭐ 49

Another curated list of Python frameworks

Machine learning around business processes

Mikropml ⭐ 48

User-Friendly R Package for Supervised Machine Learning Pipelines

Aardpfark ⭐ 47

A library for exporting Spark ML models and pipelines to PFA

pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis

Sagemaker Sparkml Serving Container ⭐ 46

This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.

Open Solution Googleai Object Detection ⭐ 46

Open solution to the Google AI Object Detection Challenge 🍁

Seqtools ⭐ 45

A python library to manipulate and transform indexable data (lists, arrays, ...)

Sagemaker Pipeline ⭐ 44

Sagemaker pipeline for AWS Summit New York

Spark Ml Serving ⭐ 44

Spark ML Lib serving library

SciKIt-learn Pipeline in PAndas

Pytorch Ner ⭐ 42

Pipeline for training NER models using PyTorch.

Pyconde2019 Airflow Ml Workshop ⭐ 42

PyConDE & PyData Berlin 2019 Airflow Workshop: Airflow for machine learning pipelines.

Kedro Kubeflow ⭐ 42

Kedro Plugin to support running workflows on Kubeflow Pipelines

Soopervisor ⭐ 42

☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.

Ckoocnlp ⭐ 41

爬虫与机器学习

Common API for all "second gen" AutoML APIs: Auger.AI, Google Cloud AutoML and Azure AutoML

Sparkxgb ⭐ 40

R interface for XGBoost on Spark

Julia Workshop ⭐ 39

"Integrating Julia in real-world, distributed pipelines" for JuliaCon 2017

Ml In Production ⭐ 39

The practical use-cases of how to make your Machine Learning Pipelines robust and reliable using Apache Airflow.

Synthetic dataset generation for object-to-model deep learning

Preprocessy ⭐ 36

Python package for Customizable Data Preprocessing Pipelines

Agogosml ⭐ 35

agogosml is a flexible data processing pipeline that addresses the common need for operationalizing ML models at scale

Classification ⭐ 35

Catalyst.Classification

Beam Learning Month ⭐ 34

Automating Livestream Video Monitoring ⭐ 34

This repo presents a demo application for realtime livestream video quality monitoring using AWS serverless and AI/ML services.

Auto Labeling Pipeline ⭐ 34

doccano auto labeling pipeline helps doccano to annotate a document automatically.

Pipeline Editor ⭐ 32

Cloud Pipelines Editor is a web app that allows the users to build and run Machine Learning pipelines without having to set up development environment.

Cifar 10 ⭐ 32

Use the famous CIFAR-10 dataset to train a multi-layer neural network to recognize images of cats, dogs, and other things.

NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.

Spark Ai ⭐ 31

Toolbox for building Generative AI applications on top of Apache Spark.

The recommendation engine for Python software stacks and Dependency Monkey in project Thoth.

Mlf Core ⭐ 31

CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow.

Kubeflow Data Science On Steroids ⭐ 30

The blog post about Kubeflow, including all materials

Demo Bank Customer Churn ⭐ 30

Demo DVC project training a classification model on tabular data

Content for ML REPA MeetUps

Sparkdltrigger ⭐ 28

Repo for the article "Machine Learning Pipelines with Modern Big DataTools for High Energy Physics"

Predict Fraud Using Auto Ai ⭐ 28

Use AutoAI to detect fraud

Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.

Segmentation ⭐ 27

Catalyst.Segmentation

Python automated machine learning framework.

Covalent Slurm Plugin ⭐ 26

Executor plugin interfacing Covalent with Slurm

Ml Pipeline Generator Python ⭐ 24

ML Pipeline Generator is a tool for generating end-to-end pipelines composed of GCP components so that any customer can easily migrate their local ML models onto GCP and start realizing the benefits of the cloud quickly.

100daysofmlcode ⭐ 23

Spark Intro Ml Pipeline Workshop ⭐ 23

A simple introduction to using spark ml pipelines

Ml Spam Sms Classification ⭐ 23

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

Surround ⭐ 22

Surround is a framework for building AI driven microservices in Python, https://surround.readthedocs.io/en/latest/

This repository is now archived. Further development has been moved to https://github.com/medkit-lib/medkit.

Bodywork Ml Pipeline Project ⭐ 21

Deployment template for a continuous training pipeline.

Click Through Rate Prediction ⭐ 21

Kaggle's click through rate prediction with Spark Pipeline API

K3ai Core ⭐ 21

K3ai-core is the core library for the GO installer. Go installer will replace the current bash installer

Medical Image Analysis Lab (MIALab), University of Bern

Neon Workshop ⭐ 20

A Pachyderm deep learning tutorial for conference workshops

Mlops Tdsp Template ⭐ 20

Quickstart template as a fork on TDSP (https://github.com/Azure/Azure-TDSP-ProjectTempla extending the template with a suggested structure for operationalization using Azure. Includes ARM templates as IaC for resource deployment, template build and release pipelines to enable model CI/CD, template code for working with Azure ML.

Use an ensemble of variant callers to call variants from ATAC-seq data

Aws Customer Churn Pipeline ⭐ 19

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

Pipeline Editor ⭐ 19

Common pipeline-editor components used in different clients (e.g. Elyra application, Web browser extensions, etc)

Mlopsmanufacturing ⭐ 19

Demonstrate samples and good engineering practice for operationalizing machine learning solutions.

FluidML is a lightweight framework for developing machine learning pipelines.

Utilities for Neural Network training

Tf 1d 2d Resnetv1 2 Seresnet Resnext Seresnext ⭐ 18

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

Latent Semantic Analysis ⭐ 18

Pipeline for training LSA models using Scikit-Learn.

An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

Alvisnlp ⭐ 17

ALvisNLP corpus processing engine

Cancerdiscover ⭐ 17

Open-source software pipeline for cancer classification from high-throughput data using machine learning.

Zounds is a dataflow library for building directed acyclic graphs that transform audio. It uses the featureflow library to define the processing pipelines.

GitHub Action that allows you to submit a run to your Azure Machine Learning Workspace.

Nbtransom ⭐ 17

Machines and people collaborating together through Jupyter notebooks.

Topcuoglu_ml_mbio_2020 ⭐ 16

Best practices for applying machine learning to bacterial 16S rRNA gene sequencing data

Continuous Adaptation For Machine Learning System To Data Changes ⭐ 16

https://blog.tensorflow.org/2021/12/continuous-ada

Playground ⭐ 16

A python library consisting of pipelines for visual analysis of different sports using Computer Vision and Deep Learning.

When Ml Pipeline Meets Hydra ⭐ 16

Smartpipeline ⭐ 16

A framework for rapid development of robust data pipelines following a simple design pattern

Tfx Kubeflow Pipelines ⭐ 15

Kubeflow pipelines built on top of Tensorflow TFX library

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