machine-learning-pipelines

There are 9 repositories under machine-learning-pipelines topic.

• ClimbsRocks / auto_ml

  [UNMAINTAINED] Automated machine learning for analytics & production

  machine-learningdata-scienceautomated-machine-learninggradient-boostingscikit-learnpythonmachine-learning-pipelinesmachine-learning-libraryproduction-readyautomllightgbmanalyticsfeature-engineeringhyperparameter-optimizationdeep-learningxgboostkerasdeeplearningtensorflowartificial-intelligence
  Language:Python 1638

• yzhao062 / combo

  (AAAI' 20) A Python Toolbox for Machine Learning Model Combination

  machine-learningdata-miningdata-scienceensemble-learningpythonmodel-combinationaggregationpipeline-frameworkmachine-learning-pipelines
  Language:Python 633
• distributed-ml-patterns

  terrytangyuan / distributed-ml-patterns

  Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

  machine-learningdistributed-systemscloud-computingcloud-nativedistributed-machine-learninglarge-scale-machine-learningpythontensorflowkubernetesargo-workflowskubeflowmachine-learning-pipelinesmanning-publicationsbookdata-sciencedevopsmlopsargo
  Language:Python 331

• PacktWorkshops / The-Data-Science-Workshop

  A New, Interactive Approach to Learning Data Science

  binaryclassificationclusteranalysisdata-preparationdatasciencedimensionality-reductionensemble-learning-feature-engineeringhyperparameter-tuning-machine-learningmachine-learning-pipelinespythonrandom-forestregression
  Language:Jupyter Notebook 188

• MLBazaar / MLPrimitives

  Primitives for machine learning and data science.

  machine-learningautomlhyperparameter-tuningpipelinesmachine-learning-pipelinesprimitives
  Language:Python 69

• AlexIoannides / pipeliner

  Machine learning pipelines for R.

  machine-learningmachine-learning-pipelinestransform-functionsrstatisticsdata-sciencepipelinepredictionworkflow
  Language:R 67

• bmabey / provenance

  Provenance and caching library for python functions, built for creating lightweight machine learning pipelines

  pythoncachingprovenancemachine-learning-pipelines
  Language:Python 33

• uzaymacar / exemplary-ml-pipeline

  Exemplary, annotated machine learning pipeline for any tabular data problem.

  data-cleaningdata-imputationdata-visualizationfeature-encodingfeature-engineeringfeature-scalingfeature-selectionfeaturetoolsh2omachine-learning-pipelinesmodelingsklearn
  Language:Jupyter Notebook 25

• vchaparro / wind-power-forecasting

  Wind Power Forecasting using Machine Learning techniques.

  windwind-power-forecastingenergyforecastingkedromachine-learning-pipelinespipelinesdata-science-challengemlflow-tracking-serversvmknnrandom-forestmarsann
  Language:Python 24

• lsjsj92 / kubeflow_example

  kubeflow example

  deep-learningdockerfilekubeflowkubeflow-pipelinesmachine-learningmachine-learning-pipelinesmlmlopspythonpython3
  Language:Python 19

• charumakhijani / spark-ml-deployment

  batch-predictionmachine-learning-pipelinesml-deploymentml-productionspark
  Language:Jupyter Notebook 11

• boschresearch / ExeKGLib

  Python library for Executable Machine Learning Knowledge Graphs

  data-scienceknowledge-graph-constructionmachine-learningmachine-learning-pipelinespython
  Language:Python 9

• Ezzaldin97 / Batch-Serving-ML-Pipeline

  create a robust, simple, effecient, and modern end to end ML Batch Serving Pipeline Using set of modern open-source/free Platforms/Tools

  batch-processingdata-version-controlexperiment-trackingforecastingmachine-learningmachine-learning-applicationmachine-learning-pipelinesmlopsmodel-monitoringscheduling
  Language:Python 8

• simplybusiness / code-first-pipelines

  A code-first way to define Ploomber pipelines

  data-pipelinesmachine-learning-pipelinesploomber
  Language:Python 7

• awesome-mlops / awesome-mlops-kubernetes

  A curated list of awesome open source tools and commercial products that will help you train, deploy, monitor, version, scale, and secure your production machine learning on kubernetes 🚀

  deep-learningkubernetesmachine-learningmlmlopsoperatordataopsmachine-learning-operationsmachine-learning-pipelinesmachine-learning-projectsmachine-learning-trainingmachine-learning-workflowml-pipelineml-workbenchmodel-managementmodel-monitoringmodel-trainingorchestrationworkflow
  5

• ZIYU-DEEP / Predicting-Terrorist-Attack-Using-Machine-Learning

  This project provides a machine learning pipeline to predict terrorist attack.

  terrorist-attacksmachine-learning-pipelinesrnn-pytorch
  Language:Jupyter Notebook 5

• gperakis / Sentiment-Analysis-On-Customer-Reviews

  Sentiment analysis on customer reviews using machine learning and python

  sentiment-analysismachine-learningglove-embeddingsclassification-reportpython3pythontext-analyticsmachine-learning-pipelines
  Language:Python 4

• guiferviz / recipipe

  Improved pipelines for data science projects.

  data-sciencepreprocessingmachine-learningsklearnmachine-learning-pipelinespipeline
  Language:Python 4

• Maoelan / ml-pipeline-human-stress-prediction

  Dicoding Submission Machine Learning Operations (MLOps) - First project Human Stress Prediction

  detection-modeldicoding-submissionembedding-layersmachine-learningmachine-learning-pipelinespipelinesubmission-dicodingtensorflow-extendendjupyter-notebookspython
  Language:Jupyter Notebook 4

• Maoelan / ml-pipline-diabetes-classification

  Dicoding Submission Machine Learning Operations (MLOps) - Final project Diabetes Classification

  jupyter-notebookmachine-learningpipelinepythonclassificationdicoding-submissionmachine-learning-pipelinessubmission-dicodingtensorflow-extendend
  Language:PureBasic 4

• aNdr3W03 / Disaster-Tweets-Classification

  Machine Learning Operations - Disaster Tweets Classification

  dicodingdockermachine-learningmachine-learning-pipelinesnlppythontensorflowtensorflow-servingtfxpipelinestfmatensorflow-extendedtfx
  Language:Jupyter Notebook 2

• aNdr3W03 / Stroke-Disease-Detection

  Machine Learning Operations - Stroke Disease Detection

  dicodingdockermachine-learningmachine-learning-pipelinespythontensorflowtensorflow-servingtfmatfxtfxpipelinestensorflow-extendendprometheus
  Language:Jupyter Notebook 2

• aravind-selvam / ml-pipeline-using-stroke-data

  This project demonstrates the implementation of a ML pipeline and CI/CD using data on heart strokes. The pipeline includes data preprocessing, model training and evaluation, and deployment. The project leverages GitHub for version control and integration with GitHub actions for efficient and automated model updates.

  cicdmachine-learningmachine-learning-pipelinesml-pipeline
  Language:Jupyter Notebook 2

• ezekielolugbami / ml_pipeline_from_scratch

  Building machine learning pipelines with procedural programming, custom-pipeline or third-party code using the titanic data set from Kaggle

  kagglelearningmachine-learningmachine-learning-models-deploymentmachine-learning-pipelinespipelinespython
  Language:Python 2

• Fengjun-Wang / IJCAI-17-customer-flow-forecasts

  Predict the customer flow (user payments) per day during the next 14 days for each shop on Koubei.com. Top 5% ranking solution for a Tianchi big data competition.

  time-seriesxgboostiterative-methodsdirectivevisualizationmachine-learning-pipelines
  Language:Jupyter Notebook 2

• ManarAlharbi / DSND-Term2-Disaster_Response_Pipeline

  Create a machine learning pipeline, that categorizes disaster events.

  disaster-response-pipelinecategorizes-disaster-eventsdata-engineeringudacity-data-science-nanodegreepythonjupyter-notebooksqlitesqlalchemymachine-learningmachine-learning-pipelinesextract-transform-loaddata-sciencenltkgridsearchcvdata-pipelinesideintegrated-development-environmentflask-webappdata-cleaning-pipelinenatural-language-processing
  Language:Jupyter Notebook 2

• ObinnaIheanachor / Disaster-Response

  This repository contains project files for a Flask app that classifies disaster messages into relevant categories.

  udacity-nanodegreepythonflaskplotlydisaster-responsenlpmachine-learning-pipelines
  Language:Jupyter Notebook 2

• OthmanMohammad / ML-AutoTrainer-Engine

  ML AutoTrainer Engine, developed using Streamlit, is an advanced app designed to automate the machine learning workflow. It provides a user-friendly platform for data processing, model training, and prediction, enabling a seamless, code-free interaction for machine learning tasks.

  auto-mlmachine-learning-pipelinespythonstreamlitweb-app
  Language:Python 2

• suryanshyaknow / APS-fault-detection

  based on the befitting sensors fetched data, prediction is to be made whether the failure in a vehicle is due to APS or some other component. Emphasis is on reducing the consequential cost by reducing the false positives and false negatives and more importantly false negatives as it appears cost incurred due to them is 50 times higher.

  airflowawsec2-instancemachine-learningmachine-learning-pipelinesmachine-learning-projectpythonsensors-data
  Language:Python 2

• AIoT-Group-UoP / crossai

  An open-source Python library for processing and developing End-to-End AI pipelines for Time Series Analysis

  data-processing-pipelinesdeep-learningdigital-signal-processingmachine-learningmachine-learning-pipelinesopen-source
  Language:Jupyter Notebook 1

• anudeepvanjavakam1 / disaster_response_NLP

  This Project is in collaboration with Figure Eight. The dataset contains pre-labelled tweets and messages from real-life disaster events. The project aim is to build a Natural Language Processing (NLP) model to categorize messages on a real time basis.

  etl-pipelineflaskhtml-css-javascriptjupyter-notebookmachine-learningmachine-learning-pipelinesnlpnlp-datasetsnlp-machine-learningnltk-pythonpickleplotlypythonscikit-learnsqlalchemy-python
  Language:Jupyter Notebook 1

• jananiarunachalam / Machine-Learning-Engineer-Udacity

  Udacity Nanodegree Exercises and Projects

  awsaws-lambdaamazon-s3aws-ec2udacity-machine-learning-nanodegreesagemakermachine-learningsoftware-engineeringsagemaker-deploymentmachine-learning-pipelinesmachine-learning-production
  Language:Jupyter Notebook 1

• joshuayeung / Disaster-Response-Pipelines

  Data Engineering Project of Udacity Data Scientist Nanodegree

  udacityudacity-nanodegreedata-engineeringmachine-learning-pipelines
  Language:Python 1

• suryanshyaknow / faulty-wafer-component-detection

  data fetched by wafers (thin slices of semiconductors) is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not. Wafers are predominantly used to manufacture solar cells and are located at remote locations in bulk and they themselves consist of few hundreds of sensors.

  airflowawsec2-instancemachine-learningmachine-learning-algorithmsmachine-learning-pipelinesmachine-learning-projectpythonwafer-defectswafers
  Language:Jupyter Notebook 1

• vadimkantorov / tritoninfererenceserverstringprocprimer

  Example string processing pipeline on Triton Inference Server

  machine-learning-pipelinespythontriton-inference-server
  Language:Python 1

• pregismond / build-ml-pipeline-airfoil-noise-prediction

  Final Project Submission: Build a Machine Learning Pipeline for Airfoil Noise Prediction

  courseraibm-skills-networkpythonapache-sparkmachine-learningmachine-learning-pipelinessparkml
  Language:Jupyter Notebook