By Tirthajyoti Sarkar – 10 min read
Mathematics is the bedrock of any contemporary discipline of science. It is no surprise then that, almost all the techniques of modern data science (including all of the machine learning) have some deep mathematical underpinning or the other.
Why Automated Feature Engineering Will Change the Way You Do Machine Learning
By William Koehrsen – 11 min read
Automated feature engineering will save you time, build better predictive models, create meaningful features, and prevent data leakage
Drake – Using Natural Language Processing to understand his lyrics
By Brandon Punturo – 8 min read
Every couple of years there is an artist who seems to take the world by storm. In the past, this has been The Beatles and Michael Jackson, among others. These artists have the intrinsic ability to influence millions with their creative genius.
Loading Data from OpenStreetMap with Python and the Overpass API
By Nikolai Janakiev— 9 min read
Have you ever wondered where most Biergarten in Germany are or how many banks are hidden in Switzerland? OpenStreetMap is a great open source map of the world which can give us some insight into these and similar questions. There is a lot of data hidden, full of useful labels and geographic information, but how do we get our hands on the data?
Web Scraping TripAdvisor, Text Mining and Sentiment Analysis for Hotel Reviews
By Susan Li – 10 min read
Study after study has shown that TripAdvisor is becoming terrifyingly important in a traveler’s decision making process. However, understanding the nuance of TripAdvisor bubble score vs. each of thousands of TripAdvisor review text , can be challenging.
Introduction to NLP
By Niklas Donges – 11 min read
Natural language processing (NLP) is an area of computer science and artificial intelligence that is concerned with the interaction between computers and humans in natural language. The ultimate goal of NLP is to enable computers to understand language as well as we do.
Getting started with graph analysis in Python with pandas and networkx
By Félix Revert – 5 min read
Graph analysis is not a new branch of data science, yet is not the usual "go-to" method data scientists apply today. However there are some crazy things graphs can do. Classic use cases range from fraud detection, to recommendations, or social network analysis.
"Data Science A-Z from Zero to Kaggle Kernels Master"
By Leonardo Ferreira – 13 min read
I’m from Brazil and many people of all world get in touch with me to ask for tips to learn or get a vacant job in the area of data science, so I decided to write this text to have something a bit more "structured" and contribute in the better way with people who are in the beginning of this journey.