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)
- clustering
- Recommender system
- content based
- collaborative based
✓ Link to the notebook: Link
- 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.