データサイエンスチュートリアル

Boost your machine learning results and discover ensembles in R with the SuperLearner package: learn about the Random Forest algorithm, bagging, and much more!

Implement a small blockchain in R and learn more about what a blockchain looks like and some of the core concepts behind it!

Learn to set up a data science environment on Google Cloud: create an instance on Google Compute Engine, install Anaconda and run Jupyter notebooks!

Dive into the lyrics of Prince's music with R: use text mining and Exploratory Data Analysis (EDA) to shed insight on The Artist's career.

In this tutorial, data science meets Search Engine Marketing: learn to create Google AdWords campaigns by generating keywords and ad templates with Python!

With this beginner tutorial, you'll start to explore PEP-8, Python's style guide, so that you can start formatting your code correctly to maximize its readability!

In this tutorial, you'll learn all about Python Strings: slicing and striding, manipulating and formatting them with the Formatter class, f-strings, templates and more!

Get Google Trends data of keywords such as 'diet' and 'gym' and see how they vary over time while learning about trends and seasonality in time series data.

Learn how feature engineering can help you to up your game when building machine learning models in Kaggle: create new columns, transform variables and more!

Which shell commands do data scientists use nearly every day? Discover and learn how to use them in this tutorial!

Learn how to build your first machine learning model, a decision tree classifier, with the Python scikit-learn package, submit it to Kaggle and see how it performs!

In this Kaggle tutorial, you'll learn how to approach and build supervised learning models with the help of exploratory data analysis (EDA) on the Titanic data.