This repository contains jupyternet notebooks for guided projects completed as part of 2 learning tracks on Dataquest.
- Cleaning and analyzing used car listings from eBay Germany
- Visualising the impact of COVID-19 on Euro-USD exchange rates
- Visualising traffic patterns on the I-94
- Analysing CIA Factbook data with SQL
- Answering business questions at a music store using SQL
- Identifying popular topics on Data Science Stack Exchange
- Identifying profitable app profiles for the App Store and Google Play markets
- Identifying the most popular Hacker News articles
- Functions for calculating different probabilities of winning the lottery
- Strategies for winning Jeopardy
- Analysing the accuracy of Fandango movie ratings
- Identifying the best markets to advertise e-learning products in
- Building a Naive Bayes SMS spam filter
- Predicting house prices with linear regression
- Predicting car prices with k-nearest neighbours
- Predicting bike rentals with linear regression, decisions trees and a random forest regressor
- Predicting the survival of Titanic passengers (Kaggle competition
- Building a handwritten digits classifier with neural networks
- Building a stack algorithm to evaluate numerical expressions
- Building a pipeline to identify the top 100 words in Hacker News posts
- Implementing a key-value database
- Analysing Startup Fundraising Deals from Crunchbase
- Analysing Stock Prices from Yahoo! Finance
- Analysing scraped data from Wikipedia pages
- Processing dataframes in chunks