Awesome-ML-Projects

Learn it by doing it!

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Lessons learnt

• Check this out for a list of lessons learnt covering:
  • Data
  • Project management
  • Model training
  • Classification
  • Training
  • Recommender system
  • Baises
  • Time series
  • Deep Learning

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Failed projects

• Failed ML Project - How bad is the real estate market getting? Article | Code

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Hardware

• Building a Raspberry Pi Cluster for QSTrader using SLURM - Part 1 | Part 2 | Part 3 | Part 4

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Rest API

• Image segmentation and Flask deployment - Article&Code
• FastAPI Machine Learning Model Service on Azure Kubernetes Cluster - Article&Code
• How to deploy a pre-trained model on the CIFAR-10 dataset wrapper around a Flask server, Dockerise it and deploy it on a Kubernetes cluster - Article

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NLP

• Big data pipeline for user sentiment analysis on US stock market - Code
• How to Deploy NLP Models in Production - Article&Code | Notes

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Public server deployment

• Model deployment using Flask and Heroku - Article | Code
• Web Application to Extract Topics from Audio with Python with Streamlit and Heroku- Article&Code
• Bitcoin price predictor using Flask and Pythonanywhere Artivle&Code
• Salary regressor using Flask and Pythonanywhere Article&Code
• Easily Deploy Your Machine Learning Model into a Web App Using Netlify Article | Code

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Pipelines

• A full E2E description of a deployed ML for stock market allocation - Article
• Building a Data Engineering Project in 20 Minutes for real estate data - Article | Code

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Cloud service: AWS

• Fine tune a LLM model, deploy it on AWS and monitor its peformances Code | Article | Notes
• AI in the cloud Blog

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Cloud service: Microsoft Azure

• A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment - Article&Code

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Cloud service: Google Cloud

• How to build an MLOps pipeline for a model that predicts the number of Bitcoin transactions per hour and put it into production with GitHub, GitHub Actions, and Google Cloud - Article | Code

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Others

• Deploying ML Models Using Kubernetes on your local machine - Article | Code

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Books focused on deployment

• Deep Learning in Production, Design, develop, train, deploy, scale and maintain your Machine Learning models

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Other resources

• Deep-Learning-in-Production

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