An Analysis of IMDb.com's database with the goal of understanding the market and elaborating a strategy to enter this industry.
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Updated
Nov 11, 2020 - Jupyter Notebook
An Analysis of IMDb.com's database with the goal of understanding the market and elaborating a strategy to enter this industry.
A data science project utilizing machine learning to predict movie release years and genres based on directors' previous works.
Understanding how movie genres can affect your return on investment
Developed an interactive Power BI dashboard to analyze the factors influencing IMDB movie success. Statistical analysis of genres, language, duration, director, and budget, revealing impact on IMDB scores. Provided valuable insights to producers, directors, and investors for decision-making in the film industry.
Movie Insights: Exploring film industry trends and analytics through data analysis techniques.
This repository includes my IMDb Web Scraping-Flatiron School Module 1 Project. In this project, I incorporated data scraping, data wrangling, data cleaning, and visualization techniques.
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