some work from Machine Learning Foundations: A Case Study Approach - univ of washington coursera course https://www.coursera.org/learn/ml-foundations this is 1st course in specialization "Machine learning - univ of washington"

concepts of machine learning like

• Regression
  • Case : House price prediction (week2)
• Classification
  • Case : Amazon product review - Sentiment analysis (week3)
• Clustering
  • Case : Wikipedia document retrieval (week4)
• Recommender systems
  • Case : Music remmonder system (week5)
• Deep learning - image search
  • Case : Image classification and Image retrieval(week6)

have been studied by case and python code for each using public datasets is implemented. Python code implemented in "Jupyter notebooks" for ease of use

Note: ipynb files in github do not render images(graphs or other images). Run locally in jupyter ipython notebook, to open the images