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This repository contains Machine Learning projects that involve the steps starting from data collection to deployment

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pratik-276/End-to-End-Machine-Learning-Projects

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Machine Learning

📌 Introduction

In most cases machine learning gets limited to the same call, fit, predict loop. Whereas ML is actually much more than that. This repository will be a place containing multiple ML projects which involves all the steps starting from data collection to final model deployment. Each of the projects have a separate readme file attached to them which will be explaining the steps to follow for recreating the project on your own system.

Contents

  1. Data collection (present or scraped)
  2. Data Cleaning
  3. Data Wrangling
  4. Data Analysis
  5. Data Visualization
  6. EDA
  7. Outlier Detections
  8. Creating ML model
  9. Deployment of the model

Projects Completed

  1. Iris Flower Classification Project
  2. GuessTheFootballer Project
  3. Breast Cancer Classification Project

More projects coming up soon. Do drop a ⭐ if you like it.

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This repository contains Machine Learning projects that involve the steps starting from data collection to deployment

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