This chapter focuses on applying data science and machine learning techniques to real-world problems using Python. It covers four main applications: clinical data analysis, social media data collection and analysis, and large-scale data processing.
The chapter begins with exploring clinical data from a dermatology study, demonstrating visual exploration, gradient descent regression, random forest classification, and k-means clustering techniques. It then transitions to social media analysis, specifically working with Reddit APIs to collect and analyze posts, examining relationships between variables like post length, scores, and upvotes.
The YouTube section covers API authentication and data collection for video statistics analysis. Finally, the Yelp analysis demonstrates big data processing techniques, exploring user behavior patterns through correlation analysis, regression modeling, and clustering of review data.
The chapter emphasizes practical API usage, data visualization, statistical testing, and the importance of understanding both the problem and data before analysis.
