Skip to main content

24 posts tagged with "tutorials"

View All Tags

· 4 min read

Project completed in week 2 (05.10.-09.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.

On the second week of the bootcamp, we started with Machine Learning (ML). If you think about it, ML surrounds us in everyday life: Netflix recommending you movies you might like, your smartphone camera detecting faces, self-driving cars recognizing passengers on the street, bank detecting credit card fraud -- these are all applications of ML. They can be split into three main ML categories:

  • Classification: Logistic Regression, Decision Trees, Random Forest
  • Regression: Linear Regression, Regression Trees, SVR, Forecasting
  • Unsupervised: PCA, Clustering, t-SNE, Matrix factorization

This week we focused only on classification and applied logistic regression, decision tree, and random forest models on the Titanic dataset to predict passenger survival.

· 3 min read

Project completed in week 1 (28.09.-02.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.

Our first bootcamp project was creating an animated scatterplot, using the libraries matplotlib or seaborn and imageio. The scatterplot illustrates the relationship between life expectancy and fertility rate of world's countries from 1960 to 2015, based on the Gapminder data set.

· 5 min read

Web scraping is a method of automatically gathering data from websites in a structured manner and storing it into a local database or spreadsheet. Why would you do this? Because you're lazy. Or because it's really impossible to copy-paste all the data you need from the website.

Some popular use-cases of web scraping are price comparison sites of products from different companies, lead generation from collected contact information, trend analysis of popular topics in a certain location. I simply wanted to see what are the most popular movies of 2018 and what features they have.