Análisis y visualización de datos con R de historial de actividad en Netflix de una cuenta personal. Visualización de maratones de series más vistas y frecuencia de actividad por días, meses y años

Production-style Netflix data lakehouse platform built on AWS, implementing a Medallion (Bronze–Silver–Gold) architecture to transform raw data into analytics-ready datasets. The pipeline leverages AWS Glue for scalable ETL processing, S3 as a data lake storage layer, Athena for serverless SQL analytics & Automated Glue workflows for Orchestration.

A notebook for movie and TV show recommendations using Boolean and TF-IDF methods. Get personalized suggestions based on text descriptions and choose the method that suits your preferences.

This is the Netflix Analysis till 2021 mid, done using Python. Read the "readme" file for a quick overview of the conslusions.

A comprehensive exploration of Netflix movies & TV shows and mobile datasets, featuring univariate, bivariate, and multivariate analyses. Visualizations and insights showcase trends, correlations, and patterns in the data.

Netflix Data Analysis based on Age Based Ratings and Top Genres of 2021 of Movies - TV Shows along side Data Visualization

Data warehousing project from identifying business opportunities, researching for data, designing, data modeling, performing data Extraction, Transformation, Loading using Python, building analytics in Tableau and made recommendations to optimize business strategies. Netflix is not only a successful Service But it is completely a Data-Driven

Stock Price Prediction

EDA of Netflix Dataset in Julia

This project performs Exploratory Data Analysis (EDA) on the Netflix Movies and TV Shows dataset to uncover trends in content distribution, growth patterns, genres, and audience targeting. The analysis focuses on transforming raw data into meaningful insights using data cleaning, visualization, and statistical reasoning

Netflix Unlocked Build | Access All Content | Watch Offline | Pre-Activated Lifetime License

Performed Analysis and Visualization on the NETFLIX TV SHOWS AND MOVIES Dataset. Data taken from Kaggle ( https://www.kaggle.com/datasets/shivamb/netflix-shows). @RaofaizanAPSACS

A tutorial-style repository to master network analysis in Python using real-world Netflix collaboration data. Learn to construct, analyze, and visualize evolving networks with networkx, track temporal trends, and detect communities — perfect for aspiring data scientists and SNA enthusiasts.

Proyecto de Ciencia de Datos orientado al análisis exploratorio, visualización y clasificación automática de contenido audiovisual disponible en Netflix.

A production-ready Movie Recommendation Engine built with Collaborative Filtering (SVD Matrix Factorization) using scikit-surprise, containerized and deployed with a responsive Gradio web interface on Hugging Face Spaces.

An Exploratory Data Analysis (EDA) of Netflix's 2021 content catalog using the Kaggle dataset. This project covers data cleaning, content categorization, and temporal and geographic insights. The analysis explores trends in Netflix's movies and TV shows, including ratings, genres, release patterns, and geographic production distribution.

The project is to simulate Real-time streaming for movie details using Kafka. We used different technologies such as Python, Amazon EC2, Apache Kafka, Glue, Athena, and SQL.

This repository features in-depth analyses and insightful observations obtained from a Netflix dataset. It provides a comprehensive overview of user preferences, content trends, and more. The analysis used dynamic charts, graphs, and dashboards to uncover patterns, correlations, and key metrics in streaming entertainment.

EDA and visualizations conducted over the Netflix dataset.