machine-learning-engineering

There are 4 repositories under machine-learning-engineering topic.

• stas00 / ml-engineering

  Machine Learning Engineering Open Book

  pytorchslurmlarge-language-modelsllmmachine-learningscalabilitytransformersmachine-learning-engineeringmlopsai
  Language:Python 9928
• kedro

  kedro-org / kedro

  Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

  pipelinekedrohacktoberfestmlopsexperiment-trackingpythonmachine-learningmachine-learning-engineering
  Language:Python 9396

• kelvins / awesome-mlops

  :sunglasses: A curated list of awesome MLOps tools

  aiawesomedata-sciencemachine-learningmachine-learning-engineeringmlmlemlops
  Language:Python 3619

• decodingml / llm-twin-course

  🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

  awsbytewaxcomet-mlcoursedockergenerative-aiinfrastructure-as-codelarge-language-modelsllmopsmachine-learning-engineeringml-system-designmlopspulumiqdrantqwakragsuperlinked
  Language:Python 655

• kennethleungty / MLOps-Specialization-Notes

  Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

  mlopsmachine-learning-engineeringandrew-ngdeeplearningaicourseramachine-learningmachine-learning-opsml-engineeringml-engineering-for-productiondeep-learningnotescoursedata-science
  338
• frouros

  IFCA-Advanced-Computing / frouros

  Frouros: an open-source Python library for drift detection in machine learning systems.

  drift-detectionconcept-driftmachine-learningpythonstatisticsdata-driftmlopsmachine-learning-engineeringmachine-learning-operationsdataset-driftdataset-shiftmlechange-detectiondistribution-shift
  Language:Python 164

• decodingml / articles-code

  💻 Decoding ML articles hub: Hands-on articles with code on production-grade ML

  mlopscomputer-visionlarge-language-modelsmachine-learning-engineeringml-system-designsystem-design
  Language:Jupyter Notebook 53

• ironcladgeek / prAIce

  A framework for forecasting stock prices with emphasis on Machine Learning best practices.

  automlforecastingmachine-learning-engineeringmlmlopspythonstock-price-prediction
  Language:Python 30

• curiousily / Hackers-Guide-to-Deep-Learning

  Tutorials on how to engineer Machine Learning projects using Deep Neural Networks with PyTorch and Python

  deep-learningmachine-learningmachine-learning-apimachine-learning-deploymachine-learning-engineeringneural-networkspythonpytorch
  Language:Jupyter Notebook 29

• iesahin / xvc

  A robust (🐢) and fast (🐇) MLOps tool for managing data and pipelines in Rust (🦀)

  command-line-tooldatadata-engineeringdata-pipelinesdata-sciencedevopsmachine-learningmachine-learning-engineeringmlopsrust
  Language:Rust 22
• MLZoomcamp2022

  MemoonaTahira / MLZoomcamp2022

  My repo for the Machine Learning Engineering bootcamp 2022 by DataTalks.Club

  bentomldeep-learningdeploymentdockermachine-learningmachine-learning-engineeringpythonaws-ec2aws-fargateaws-lambdakservekubernetestensorflow-servingtflite
  Language:Jupyter Notebook 22

• Techn0logic / kubeflow-pipelines-standalone

  A Helm chart containing Kubeflow Pipelines as a standalone service.

  mlopsmlops-workflowmachine-learning-engineeringkubeflow-pipelinesworkflow-enginemachine-learning
  8

• andreizolotarev / MLOps

  This repository contains examples of using various libraries/tools for MLOps.

  mlopsmlops-workshopmlemachine-learningmachinelearningengineeringmachine-learning-engineeringdata-sciencedockermlflowdvcredisailuigiairflowflask
  Language:Python 5

• cedrickchee / baselines

  OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

  reinforcement-learningopenai-gymppodeep-learningdota2-botpolicyself-playopenai-fivemachine-learning-engineeringproximal-policy-optimizationpolicy-gradienttrpoalgorithms
  Language:Python 4

• jagadishmali567 / BCG-Open-Access-Data-Science-Advanced-Analytics-Virtual-Experience-Program

  The tasks I was required to complete as a part of the BCG Open-Access Data Science & Advanced Analytics Virtual Experience Program are all contained in this repository. 📊📈📉👨‍💻

  business-understandingclient-communicationcommunicationcreativitydata-visualizationexploratory-data-analysishypothesis-framingjupyter-notebooksmachine-learning-algorithmsmachine-learning-engineeringmathematical-modellingmatplotlib-pyplotmodel-evaluationmodel-interpretationprogrammingpython-3seabornsynthesisfeature-engineeringstatistical-analysis
  Language:Jupyter Notebook 3

• prakharrathi25 / mlops-specialization-coursera

  Machine Learning for Production Specialization

  machine-learningmooc-solutionsproductioncourseramachine-learning-engineeringmlopspythonhacktoberfest
  3

• alanchn31 / Flower-App

  Flower Classification Web Application (Built with Flask)

  deep-learningimage-classificationmachine-learning-engineering
  Language:Python 2

• abhisrn1986 / TwitterDataPipeline

  The project comprises a real-time tweets data pipeline, a sentimental analysis of the tweets module, and a Slack bot to post the tweets' sentiments. The project uses SentimentIntensityAnalyzer from the VaderSentiment library. The analyzer gives positive, negative, and compound scores for small texts (such as tweets in this case). The real-time data pipeline flow is as follows: 1.Tweets are collected and stored in a database. 2.The sentiment of the tweets is analyzed. 3.The tweet sentiment is posted on a Slack channel using a Slack bot.

  data-pipelinedata-sciencedockerdocker-composemachine-learning-engineeringmachine-learning-operationsmongodbpipelinepythonreplicasetsentiment-analysisslackslackbottweepytweepy-apitweetsvader-sentiment-analysisdocker-filedocker-imageshell-scripting
  Language:Python 1

• autgaard / data-science-misc-projects

  Here you will find a selection of miscellaneous data science projects that are not included in my project portfolio.

  data-cleaningdata-analysispythondata-sciencejupyter-notebookdata-visualizationmachine-learningmachine-learning-algorithmsmachine-learning-engineeringsql
  Language:Jupyter Notebook 1

• gabrieltardochi / full-stack-deep-facial-recognition

  Leverage Metaflow, PyTorch, AWS S3, Elasticsearch, FastAPI and Docker to create a production-ready facial recognition solution. It demonstrates the practical use of deep metric learning to recognize previously unseen faces without prior training.

  artificial-intelligenceawsface-recognitionfacial-recognitionfastapimachine-learning-engineeringmetaflowmetric-learningtriplet-lossapproximate-nearest-neighbor-searchcnndeep-learningdockerdocker-composeelasticsearch
  Language:Python 1

• joabara / Iridium-Crypto-Trader

  An cryptocurrency trading bot that uses automated machine learning for decision making to maximize returns.

  machine-learningalgorithmic-tradingcryptocurrencybotsmachine-learning-engineering
  Language:Python 1

• labrijisaad / AXA-Direct-ML-Apprenticeship

  Repository showcasing my Machine Learning Engineering Apprenticeship at AXA-Direct Assurance, contributing to the development and implementation of Machine Learning solutions.

  azure-devopsdata-driftdatabricksjupyter-notebookkedromachine-learningmachine-learning-engineeringmlflowpython
  1

• caiquemiranda / machine-learning-engineering-python

  machine-learningmachine-learning-algorithmsmachine-learning-engineeringmlopsneural-network
  Language:Jupyter Notebook 0

• jrpespinas / sales-prediction

  Develop a single endpoint to predict the sales of a company

  machine-learning-engineeringmlops
  Language:Jupyter Notebook 0

• JuniorTorresMTJ / model_api_mlops_project

  This project aims to apply MLOps techniques to deploy a machine learning model through an API constructed with FastAPI. We utilize Poetry for dependency management and Docker for containerization, ensuring the code is modular, organized 📐, and maintainable 🛠️.

  dockerfastapimachine-learningmachine-learning-algorithmsmachine-learning-engineeringmkdocsmlopspython3
  Language:Python 0

• kennymassie / resume

  My professional resume

  aiarchitectbig-dataclouddata-scienceengineermachine-learningmachine-learning-engineeringmanagementmlopsresume
  0

• riccardoprosdocimi / forage-cognizant-ai

  Cognizant Artificial Intelligence job simulation on Forage.

  communicationdata-analysisdata-modelingdata-visualizationdevelopmentevaluationmachine-learningmachine-learning-engineeringmodel-interpretationproblem-statementpythonpython3quality-assurance
  Language:Jupyter Notebook 0
• sun-analytics.github.io

  Sun-Analytics / sun-analytics.github.io

  The website of Sun Analytics B.V.

  data-sciencemachine-learning-engineeringdata-engineeringconsultingtraining
  Language:HTML 0

• Yingying-Hu / plagiarism-detection-project

  Udacity Project: Build an end-to-end plagiarism classification model. Apply skills to clean data, extract meaningful features, and deploy a plagiarism classifier in SageMaker.

  aws-sagemakerknn-classificationplagiarism-detectormachine-learning-algorithmsmachine-learning-engineeringudacity-nanodegree
  Language:Jupyter Notebook 0

• alejandrodebus / kueski-challenge

  Kueski Challenge - Vacante de Machine Learning Engineer

  pythondockerpysparkmlopsredisfastapiminiomachine-learningmachine-learning-opsairflowmachine-learning-engineeringmachinelearningmlmachine-learning-operations
  Language:Jupyter Notebook

• emilieallen / udacity-machine-learning-nanodegree-

  Machine Learning Model Deployment with SageMaker

  machine-learningsagemakerdeploymentdata-sciencemachine-learning-engineeringsegmentationnlp
  Language:Jupyter Notebook

• joewynn / mlops-for-fun

  Having fun with MLOPS: Wine Stuff

  deep-learningmachine-learningmachine-learning-engineeringmlopsrecommender-systemwine-quality
  Language:Python

• prajwalchapke055 / Cognizant-Artificial-Intelligence-Job-Simulation-Forage

  Advise one of Cognizant’s clients on a supply chain issue by applying knowledge of machine learning models.

  artificial-intelligencecognizantcommunicationdata-analysisdata-modelingdata-visualizationdevelopmentevaluationforagejob-simulationmachine-learningmachine-learning-algorithmsmachine-learning-engineeringmodel-interpretationpresentationproblem-statementpythonquality-assuranceskillsvirtual-internship
  Language:Jupyter Notebook

• teyang-lau / MLOps_MLflow

  End-to-end MLOps Using MLflow for ML lifecycle, including data validation, processing, model training, evaluation, validation and deployment

  machine-learning-engineeringmlflowmlopsmlops-workflow
  Language:Python

• zhermin / car-classifier

  Car Type Classifier using EfficientNetV2, Dockerized and served with FastAPI

  classificationcnnmachine-learning-engineering
  Language:Jupyter Notebook

• zhermin / emission-factor-matching

  MLE NLP Matcher that maps item descriptions in natural language to carbon emission labels and factors

  embeddingsfastapimachine-learning-engineeringnlp
  Language:Jupyter Notebook