Data Science plays a role so important in a majority of online services and helps not only bring more customers but keeps the existing ones happy. The reason why is because, with Data Science, you get a more realistic picture of your consumers’ taste in the form of graphs and charts that take not just one metric but several as input. This crucial piece of information helps you in molding your products and services in a way that looks one-of-a-kind to your customers, attracting them to your platform.
With a company like Netflix that is brimming with data, it’s always a wise decision to put that pile of data to good use. By incorporating concepts like data analysis, machine learning, statistics and deep learning, Data Science can help not just Netflix but any business to grow exponentially regardless of sector.
As Reed Hastings said:
Everyone with a phone has a screen and access to the internet. That is our addressable market. The world’s taste, and the world’s time, is what we’re after.
Data Science plays a critical role in not just deciding the functioning of Netflix but also presents them with newer opportunities to grow. New technologies often bring their fair share of issues with them, but at Netflix, they have been tackling those issues head-on, consistently by taking community inputs. By open-sourcing several of the libraries and frameworks to the community, Netflix aims to improve not just itself, but other companies as well. In the end, it would be incorrect to say that Netflix takes all its decisions based on Data Science insights as they still rely on human inputs from a lot of people.
This project aims to build a movie recommendation mechanism and data analysis within Netflix. The dataset I used here come directly from Netflix.
You can download the dataset here: Netflix Movies and TV Shows
Kaggle Notebook Link of this project
This project will be consistently be updated! Welcome any suggestions! Let's get started!
Feel free to fork and upvote if this notebook is helpful to you in some ways!