/machine-learning-6-practical-real-world-app

This repo contains the code from the course Machine Learning Practical 6 Real-World Applications

Primary LanguageJupyter Notebook

Machine Learning Practical: 6 real-world Aplications

This repository contains the code from 6 practical real cases solved with Machine Learning. The contend is related with the course Machine Learning Practical: 6 Real-World Applications created / dictated by Kirill Eremenko, Hadelin de Ponteves, Dr. Ryan Ahmed, Ph.D., MBA, SuperDataScience Team and Rony Sulca.

List of solved cases included in this this repo:

  • diagnosing diabetes in the early stages
  • directing customers to subscription products with app usage analysis (Linear Regression [L1])
  • minimizing churn rate in finance
  • predicting customer location with GPS data
  • forecasting future currency exchange rates
  • classifying fashion (Deep Learning)
  • predicting breast cancer (Support Vector Machine - SVM)

Datasets

All the datasets used in this course were downloaded from datasets & Code Course