machine-learning-pipeline

There are 2 repositories under machine-learning-pipeline topic.

• khuyentran1401 / Machine-learning-pipeline

  Example machine learning pipeline with MLflow and Hydra

  hydramachine-learning-pipelinemlflowmachine-learningdata-science
  Language:Python 83

• kennethleungty / Anomaly-Detection-Pipeline-Kedro

  Anomaly Detection Pipeline with Isolation Forest model and Kedro framework

  kedroanomaly-detectionfinancialfinancial-datacredit-cardcredit-card-fraudfraudfraud-detectionmlopsmachine-learningmachine-learning-pipelinedata-science-pipelinepipelinesanomalyquantumblackdata-scienceml
  Language:Python 20

• Arslan-Mehmood1 / Machine-learning-pipeline-deployment-using-Docker-and-FastAPI

  This project is focused on the Deployment phase of machine learning. The Docker and FastAPI are used to deploy a dockerized server of trained machine learning pipeline.

  dockerfastapimachine-learning-pipelinedockerized-servermachine-learning-productionmodel-serving
  Language:Python 18
• NBA-attendance-prediction

  wyattowalsh / NBA-attendance-prediction

  Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.

  machine-learningnbaevent-attendance-predictionmachine-learning-pipelinepythonjupyter-notebookdata-sciencedata-visualizationdata-analyticsr
  Language:Jupyter Notebook 10

• labrijisaad / Kedro-Energy-Forecasting-Machine-Learning-Pipeline

  This repo showcases a project that transforms ML model training into a simplified, production-ready Kedro Dockerized Pipeline. It emphasizes best MLOps practices, enabling easy training, evaluation, and deployment of models, including XGBoost, LightGBM and Random Forest, with built-in visualization and logging features for effective monitoring.

  cicddockerdocker-volumegithub-actionsjupyter-notebookkedrokedro-dockerlightgbmmachine-learning-pipelinemlopsmlops-workflowrandom-forestxgboost
  Language:Jupyter Notebook 6

• Vidhi1290 / Machine-learning-Pipeline

  Explore a collection of Jupyter notebooks that guide you through various stages of the machine learning pipeline. From data analysis and feature engineering to model training and deployment, these notebooks provide practical insights for both beginners and experienced data enthusiasts. Let's dive into the world of data-driven decision-making! 📊🚀"

  data-analysisfeature-engineeringfeature-selectionjupyterjupyter-notebookmachine-learningmachine-learning-algorithmsmachine-learning-pipelinemodel-trainingnew-datasetopensourcepython
  Language:Jupyter Notebook 6

• ejhusom / d2m

  A machine learning pipeline taking you from raw data to fully trained machine learning model - from data to model (d2m).

  ai-engineeringartificial-intelligencedata-sciencedata-version-controlexplainable-aigreen-aimachine-learningmachine-learning-pipelineuncertainty-estimation
  Language:Python 5

• Cutwell / spatial-data-upscaling

  Pipeline for augmenting sparse data for genetic optimisation

  genetic-algorithmmachine-learning-pipelinepipleline
  Language:Jupyter Notebook 1

• Jishnuadhikary10 / ml_hotel_booking_prediction

  The code snippet cleans and analyzes a hotel bookings dataset, handling missing values, dropping unnecessary columns, and creating new features. It visualizes the data using various plots and performs feature encoding and selection. It then trains machine learning models to predict hotel booking cancellations.

  data-analysisdata-cleaningdatasetfeature-engineeringmachine-learning-pipelinematplotlibmodel-buildingnumpypandasseabornvisualization
  Language:Jupyter Notebook 1

• khadkarajesh / wine-prediction

  White and Red Wine classification using logistic regression

  machine-learningclassificationlogistic-regressionairflowairflow-dagsscikit-learnmachine-learning-pipelinepandasnumpymlflowpostgresqldata-sciencedataingestionpipelinepythonflaskevidentlylogistic-regression-algorithmclassification-algorithmsupervised-learning
  Language:HTML 1

• oguzerdo / diabetes-prediction-ml-pipeline

  Develop a machine learning model that can predict whether people have diabetes when their characteristics are specified

  classificationdata-sciencemachine-learningmachine-learning-pipelineml-pipelinevoting-classifier
  Language:Jupyter Notebook 1

• SaM-92 / Azure_ML_Energy_Predict

  azureazure-mlazure-mlstudiocloud-computingenergy-efficiencymachine-learningmachine-learning-pipelinepipeline
  Language:Jupyter Notebook 1

• timchansdp / Disaster-Response-Pipelines

  Developed a ETL pipeline, a ML training pipeline and a Flask web app that can classify disaster-related messages input by a user.

  disaster-responseetl-pipelineflask-webmachine-learning-pipeline
  Language:Python 1

• abhipatel35 / Automated-Machine-Learning-Pipeline-for-Iris-Dataset-Classification

  Automated ML pipeline for Iris dataset classification using Decision Tree. Features PCA dimensionality reduction and standard scaling.

  automated-machine-learningclasssificationdata-preprocessingdescision-treedimentionality-reductioniris-datasetmachine-learning-pipelinepythonrandom-forestscikit-learnend-to-end-ml-workflows
  Language:Python 0

• Anashaneef / clickbait-classification-pipeline

  This is the first project of the ML-Ops Dicoding class. This project serves to classify whether a title is included in the clickbait category or not.

  clickbait-detectiondicodingdockermachine-learningmachine-learning-pipelinetf-serving
  Language:Jupyter Notebook 0

• ar8372 / Framework3

  Framework3 is a super-simple and robust ML Pipeline for tabular and image competition. The purpose of this is to make the process not too abstract, so that the user can have full control over it.

  deep-learningmachine-learningmachine-learning-pipelinekeras-tensorflowpytorch
  Language:Python 0

• eermis1 / Udacity_DisasterResponses_Project

  This repository has been created for Udacity Data Scientist Nanodegree Program - Data Engineering Part - Disaster Response Pipeline Project.

  data-sciencenlp-machine-learningpipelineetl-pipelinenlp-pipelinemachine-learning-pipelineflaskplotlywebsite
  Language:HTML 0

• heschmat / project-disaster-response

  Analyze disaster data from Figure Eight to build a model for an API that classifies disaster messages.

  etl-pipelinemachine-learning-pipelinedeploymentmachine-learningclass-imbalance
  Language:Jupyter Notebook 0

• kkaibin / disaster-response-classifier

  Classifying real messages that were sent during disaster events so that they can be sent to an appropriate disaster relief agency.

  nlpsupervised-learningetl-pipelinemachine-learning-pipeline
  Language:Python 0

• Reema-Khaseeb / car-price-prediction

  Clean and extract features from a large, scrapped data set from the Palestinian market. Deploying ML Pipeline

  fastapimachine-learningmachine-learning-pipelineml-pipelineeda
  Language:Jupyter Notebook 0

• artainmo / total_perspective_vortex

  42 school project. Process EEG datas by cleaning, extracting, creating a ML pipeline implementing a dimensionality reduction algorithm before finding the right classifier and handling a real time data-stream with sklearn.

  42schoolartificial-intelligencedecision-tree-classifierdriftinggradient-boosting-classifierknn-classificationmachine-learning-pipelinecspraw-datamnepythonstudy
  Language:Python

• Cutwell / irregular-searchspace-pipeline

  Pipeline for working with irregular search spaces in Platypus-Opt genetic optimisation

  genetic-algorithm-frameworkmachine-learning-pipelinepipelineplatypus-opt
  Language:Jupyter Notebook

• mikethwolff / ML-FastAPI

  This repository lists one of my projects and findings as part of my Machine Learning DevOps Engineer Nanodegree.

  continuous-deploymentcontinuous-integrationfastapimachine-learning-pipelinemodel-bias-analysis
  Language:Jupyter Notebook

• mxagar / disaster_response_pipeline

  This repository contains a Machine Learning (ML) pipeline which predicts the response to messages in disaster situations. An ETL pipeline is also developed and everything is deployed with a web app based in Flask.

  classificationetl-pipelineflaskmachine-learningmachine-learning-pipelinepipelinesqlite
  Language:Jupyter Notebook

• RegaipKURT / ScikitLearnWithFUN

  This repository shows the implementation of machine learning algorithms, data pipelines and data visualization with scikit-learn and python.

  machine-learningdata-sciencepythonscikit-learnscikitlearn-machine-learningscikit-learn-pythonmachine-learning-modelsdata-science-pipelinesmachine-learning-pipelinesmachine-learning-pipelinejupyter-notebookdata-visualizationdata-analysisdata-analytics
  Language:Jupyter Notebook