Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub topics: machine-learning-pipelines

Repositories

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

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

Language: Jupyter Notebook - Size: 175 KB - Last synced: 16 days ago - Pushed: 16 days ago - Stars: 0 - Forks: 0

ClimbsRocks/auto_ml

[UNMAINTAINED] Automated machine learning for analytics & production

Language: Python - Size: 1.38 MB - Last synced: 2 days ago - Pushed: over 3 years ago - Stars: 1,638 - Forks: 312

terrytangyuan/distributed-ml-patterns

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

Language: Python - Size: 2.04 MB - Last synced: 14 days ago - Pushed: 4 months ago - Stars: 322 - Forks: 32

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.

Language: Jupyter Notebook - Size: 2.19 MB - Last synced: 25 days ago - Pushed: almost 3 years ago - Stars: 2 - Forks: 1

nakshatrasinghh/CML_RedWineQuality

A continuous Machine Learning integration workflow using Github Actions. This project is based upon team collaboration for aesthetic version control for ML pipelines and deployement.

Language: Python - Size: 1.18 MB - Last synced: 27 days ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

yzhao062/combo

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

Language: Python - Size: 4.95 MB - Last synced: 8 days ago - Pushed: over 1 year ago - Stars: 632 - Forks: 106

vadimkantorov/tritoninfererenceserverstringprocprimer

Example string processing pipeline on Triton Inference Server

Language: Python - Size: 64.5 KB - Last synced: about 1 month ago - Pushed: 5 months ago - Stars: 1 - Forks: 0

kevinshen56714/Polymer-Molecular-Dynamics

Modern, fast, python framework for building LAMMPS input and data files for predicting polymer properties

Language: Python - Size: 4.15 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 1 - Forks: 0

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

Language: Python - Size: 1.67 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 4 - Forks: 1

AlexIoannides/pipeliner 📦

Machine learning pipelines for R.

Language: R - Size: 98.6 KB - Last synced: 15 days ago - Pushed: over 7 years ago - Stars: 67 - Forks: 6

suryanshyaknow/predictive-maintenance-regression-2.0

Although PdM revolves around detecting anomalies and possible defects before they happen, here, however, based on befitting predictors and machine failures, this project attempts to predict Air Temperature that in actuality is generated using random walk process, via a regression algorithm.

Language: Jupyter Notebook - Size: 6.43 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

furyhawk/sk_pipeline

sklearn pipeline

Language: Python - Size: 48.8 KB - Last synced: 18 days ago - Pushed: 4 months ago - Stars: 0 - Forks: 1

vchaparro/wind-power-forecasting

Wind Power Forecasting using Machine Learning techniques.

Language: Python - Size: 78.1 MB - Last synced: 4 months ago - Pushed: about 1 year ago - Stars: 21 - Forks: 6

MLBazaar/MLPrimitives

Primitives for machine learning and data science.

Language: Python - Size: 9.89 MB - Last synced: 22 days ago - Pushed: about 2 months ago - Stars: 69 - Forks: 38

shantanu-dahitule/MLOpsBasics

Language: Python - Size: 211 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

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

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

Language: Jupyter Notebook - Size: 170 MB - Last synced: 18 days ago - Pushed: almost 5 years ago - Stars: 4 - Forks: 8

AIoT-Group-UoP/crossai

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

Language: Jupyter Notebook - Size: 11 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 1

pranaysingh25/Titanic-Survival-Prediction

A basic classification model based on Random Forest Classifier predicting the Titanic Disaster Survival for a set of test data. Data Structure provided by Kaggle.

Language: Jupyter Notebook - Size: 237 KB - Last synced: 5 months ago - Pushed: about 4 years ago - Stars: 0 - Forks: 1

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.

Language: Python - Size: 319 KB - Last synced: 3 months ago - Pushed: 5 months ago - Stars: 2 - Forks: 0

PacktWorkshops/The-Data-Science-Workshop

A New, Interactive Approach to Learning Data Science

Language: Jupyter Notebook - Size: 169 MB - Last synced: 6 months ago - Pushed: over 1 year ago - Stars: 179 - Forks: 195

boschresearch/ExeKGLib

Python library for Executable Machine Learning Knowledge Graphs

Language: Python - Size: 2.84 MB - Last synced: 24 days ago - Pushed: 7 months ago - Stars: 8 - Forks: 3

uzaymacar/exemplary-ml-pipeline

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

Language: Jupyter Notebook - Size: 104 KB - Last synced: 4 months ago - Pushed: over 4 years ago - Stars: 24 - Forks: 7

anuragkr29/TweetAnalysis

Work with a set of Tweets about US airlines and examine their sentiment polarity.The aim is to learn to classify Tweets as either “positive”, “neutral”, or “negative” by using two classifiers and pipelines for pre-processing and model building.

Language: Scala - Size: 4.88 KB - Last synced: 9 months ago - Pushed: almost 5 years ago - Stars: 0 - Forks: 0

bmabey/provenance

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

Language: Python - Size: 503 KB - Last synced: 29 days ago - Pushed: over 3 years ago - Stars: 33 - Forks: 9

Maoelan/ml-pipeline-human-stress-prediction

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

Language: Jupyter Notebook - Size: 22.9 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

Arslan-Mehmood1/Credit-Risk-Analysis-for-european-peer-to-peer-lending-firm-Bandora

Machine Learning pipelines are deployed to accomplish the objective of credit risk analysis.

Language: Python - Size: 3.49 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

lsjsj92/kubeflow_example

kubeflow example

Language: Python - Size: 42 KB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 17 - Forks: 8

sjord01/Housing_Prediction

Machine Learning application of a of predicting housing values using regression task utilizing the SciKit-Learn extensions; the pipeline has various algorithms such as Linear Regression, Decision Trees, and Random Forests.

Language: Jupyter Notebook - Size: 907 KB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

sjord01/Image-Classification-Image-Validation

Machine learning framework using the MNIST dataset, which a set of 70,000 small images of digits handwritten by high school students and employees of the US Census Bureau.

Language: Jupyter Notebook - Size: 259 KB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 4.2 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 10.6 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 1

ObinnaIheanachor/Disaster-Response

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

Language: Jupyter Notebook - Size: 11.2 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 2 - Forks: 0

charumakhijani/spark-ml-deployment

Language: Jupyter Notebook - Size: 855 KB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 9 - Forks: 10

anudeepvanjavakam1/disaster_response_NLP

This Project is part of Data Science Nanodegree Program by Udacity in collaboration with Figure Eight. The dataset contains pre-labelled tweet 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.

Language: Jupyter Notebook - Size: 7.67 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 4.03 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

Related Keywords

machine-learning-pipelines 50 machine-learning 31 python 27 data-science 10 python3 6 mlops 4 tensorflow 4 scikit-learn 4 aws 4 pipeline 4 feature-engineering 4 docker 3 machine-learning-project 3 machine-learning-algorithms 3 pipelines 3 sklearn 3 deep-learning 3 nlp 3 data-analysis 3 airflow 2 random-forest 2 data-engineering 2 tfxpipelines 2 dockerfile 2 tfx 2 tfma 2 tensorflow-serving 2 ec2-instance 2 dicoding 2 dvc 2 wafer-defects 2 wafers 2 nlp-machine-learning 2 jupyter-notebook 2 flask 2 plotly 2 forecasting 2 udacity-nanodegree 2 xgboost 2 spark 2 sentiment-analysis 2 automl 2 kubeflow 2 tensorflow-extendend 2 data-visualization 2 feature-selection 1 featuretools 1 h2o 1 modeling 1 feature-scaling 1 disaster-response 1 dataframe 1 sensors-data 1 rdd 1 scala 1 feature-encoding 1 stopwords-removal 1 tokenizer 1 tweets 1 caching 1 provenance 1 detection-model 1 dicoding-submission 1 embedding-layers 1 matplotlib-pyplot 1 matplotlib 1 machine 1 matplot 1 jupyter-notebooks 1 ml 1 submission-dicoding 1 kubeflow-pipelines 1 credit-risk-analysis 1 amazon-s3 1 aws-ec2 1 aws-lambda 1 machine-learning-production 1 sagemaker 1 sagemaker-deployment 1 software-engineering 1 udacity-machine-learning-nanodegree 1 kaggle 1 learning 1 machine-learning-models-deployment 1 aiops 1 data-analytics 1 data-science-pipelines 1 machine-learning-models 1 machine-learning-pipeline 1 scikit-learn-python 1 scikitlearn-machine-learning 1 udacity 1 gridsearch 1 sklearn-compatible 1 validation-set 1 classification-report 1 glove-embeddings 1 text-analytics 1 batch-prediction 1 ml-deployment 1