Farhad-Davaripour / Machine_learning_with_python

The present notebook provides data analysis on several datasets using different machine learning (ML) techniques including supervised ML, unsupervised ML, and recommender system

Hands-on Practice Learning Lab for Data Science

Overview

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This repository includes several hands on labs provided as a part of Machine Learning with Python course, offered by coursera.org.

The present notebook provides data analysis on several datasets using different machine learning (ML) techniques including:

• Supervised ML
  • regression models
  • classification methods
    • K nearest neighbor
    • decision tree
    • logistic regression
    • support vector machine (SVM)
• Unsupervised ML
  • clustering
    • partition-based method (k-mean)
    • hierarchical method (Agglomerative clustering)
    • density-based method (DSSCAN method)
• Recommender system
  • content based
  • collaborative based

✓ Link to the notebook: Link

About The Author

• Farhad Davaripour is a finite element specialist/data science enthusiast with near 3 years of experience working in research and development roles. He has a knack for problem-solving and passion for data science (He is certified with IBM Data Science Professional Certificate).
• Connect with Farhad on LinkedIn.