Guided projects under Data Camp
- Mobile apps are everywhere. They are easy to create and can be lucrative.
- Because of these two factors, more and more apps are being developed.
- The data for this project was scraped from the Google Play website.
- While there are many popular datasets for Apple App Store, there aren't many for Google Play apps, which is partially due to the increased difficulty in scraping the latter as compared to the former. The data files are as follows:
apps.csv: contains all the details of the applications on Google Play. There are 13 features that describe a given app.user_reviews.csv: contains 100 reviews for each app, most helpful first. The text in each review has been pre-processed and attributed with three new features: Sentiment (Positive, Negative or Neutral), Sentiment Polarity and Sentiment Subjectivity.
- We'll look for insights in the data to devise strategies to drive growth and retention.
- Lavanya Gupta, Machine Learning Engineer at PropTiger.com
- It's not that we humans only take debts to manage our necessities.
- A country may also take debt to manage its economy.
- For example, infrastructure spending is one costly ingredient required for a country's citizens to lead comfortable lives.
- The World Bank is the organization that provides debt to countries.
- In this project, we are going to analyze international debt data collected by The World Bank.
- The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories.
- Sayak Paul, Deep Learning Associate at PyImageSearch