Skip to main content

12 Useful Data Science Walkthroughs

A curated collection of data science coding walkthroughs to get some hands-on experience solving real world problems!
Jul 2017  · 5 min read

So you’ve developed some base skills in programming, data visualization, data manipulation etc... And are looking for ways to apply those skills and build a data science portfolio?

We’re here to help.

Practicing your skills with concrete examples will boost your data science confidence and will help you identify and solve problems in the real world. For this reason, we’ve made a collection of high-quality walkthroughs ranging from Text Mining, ML, Deep Learning, Finance and more.

Check it out and let us know your favorite!

Text Mining in R

  • - learn how to use market basket analysis to find common patterns of items in large datasets. This walkthrough showcases this technique on a large online retail data set to try to find interesting purchase combinations.

    Machine Learning

    Machine Learning (ML) is increasingly becoming essential in a data scientist’s toolbox for both R and Python. Advances in ML are a big reason why data science has become such an in-demand skill. These 3 walkthroughs below show you how to use scikit-learn (Python) and Caret (R) along with a series of Machine Learning techniques.

    Scikit-Learn (Python)

    Caret (R)

    • Machine Learning in R For Beginners - This includes a walkthrough on multi-class classification with the well-known k-nearest neighbor algorithm with the help of the caret library. This short introduction to ML in R is a must for R learners and the data used here is the famous iris dataset.

    Building a Classifier

    Forecasting (Python)

    Deep Learning

    Even more so than Machine Learning, Deep Learning gets all the attention in the data science world. Companies are investing in infrastructure and talent to take advantage of this new field. To become an elite data scientist, Deep Learning is a must.

    Keras (R + Python)

    • Keras Tutorial: Deep Learning in Python - Build a Multi-Layer Perceptron (MLP) for classification and regression tasks using a wine data set.
    • keras: Deep Learning in R - The Keras package was recently launched in R, be an early adopter! Here you will build a MLP for multi-class classification again using the iris dataset.


    • TensorFlow Tutorial For Beginners (Python) - Work on Belgian traffic signs data with Google’s very own TensorFlow, one of the more promising deep learning libraries.

    Finance (Python)

    Python For Finance: Algorithmic Trading - Perform financial analysis, develop a trading strategy, and backtest it using Quantopian in this popular walkthrough.

    For more data science content, create a free DataCamp account to receive a newsletter every Tuesday with the best data science news and projects!

← Back to Blogs