In this video, I dive into an exciting project where I explore Netflix series data using Java Stream APIs. The dataset is sourced from Kaggle, providing a rich collection of information about various Netflix series, including titles, genres, release years, and more.

Through the power of Java Stream APIs, I demonstrate how to efficiently filter, sort, and analyze this data to extract valuable insights. Whether you want to find the top genres, analyze release patterns, or discover trends in series popularity, Stream APIs make it incredibly easy to handle large datasets with clean, readable code.

Key Highlights:
Overview of the Netflix dataset from Kaggle
Step-by-step walkthrough of Java Stream APIs for data processing
Real-world examples of filtering, mapping, and reducing data
Insights gained from the Netflix series dataset, such as popular genres, trends over the years, and more!
Whether you're a data enthusiast or a Java programmer looking to enhance your skills with Stream APIs, this video will show you how to combine data analysis with Java's powerful streaming features. Make sure to watch till the end for a code demo and helpful tips!


Github link https://github.com/anilgola90/Stream-...