python
+1

Python Regular Expression Tutorial

Discover Python regular expressions: find basic and complex patterns, repetitions, or to do (non-)greedy matching, work with the re library and much more!
103
103
python
+8

Kaggle Tutorial: EDA & Machine Learning

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.
90
90
r programming
+1

Fast-and-Frugal Decision Trees in R with FFTrees

An introductory tutorial to fast-and-frugal decision trees in R with the FFTrees package.
30
30
must read
r programming

Five Tips to Improve Your R Code

Five useful tips that you can use to effectively improve your R code, from using seq() to create sequences to ditching which() and much more!
must read
r programming
121
121
python

Python Dictionary Comprehension Tutorial

Learn all about Python dictionary comprehension: how you can use it to create dictionaries, to replace (nested) for loops or lambda functions with map(), filter() and reduce(), ...!
53
53
python

Python Data Structures Tutorial

Get introduced to Python data structures: learn more about data types and primitive as well as non-primitive data structures, such as strings, lists, stacks, etc.
120
120
learning data science
+2

AWS EC2 Tutorial For Beginners

Discover why you should use Amazon Web Services Elastic Compute Cloud (EC2) and how you can set up a basic data science environment on a Windows instance.
42
42
python
+4

Convolutional Neural Networks in Python with Keras

In this tutorial, you’ll learn how to implement Convolutional Neural Networks (CNNs) in Python with Keras, and how to overcome overfitting with dropout.
91
91
r programming
+2

Formulas in R Tutorial

Discover the R formula and how you can use it in modeling- and graphical functions of well-known packages such as stats, and ggplot2.
64
64
must read
r programming
+2

Pipes in R Tutorial For Beginners

Learn more about the famous pipe operator %>% and other pipes in R, why and how you should use them and what alternatives you can consider!
125
125
python
+2

Python List Comprehension Tutorial

Learn how to effectively use list comprehension in Python to create lists, to replace (nested) for loops and the map(), filter() and reduce() functions, ...!
97
97
machine learning

LDA2vec: Word Embeddings in Topic Models

Learn more about LDA2vec, a model that learns dense word vectors jointly with Dirichlet-distributed latent document-level mixtures of topic vectors.
57
57
python

Python Loops Tutorial

A comprehensive introductory tutorial to Python loops. Learn and practice while and for loops, nested loops, the break and continue keywords, the range function and more!
57
57
python
+5

Web Scraping & NLP in Python

Learn to scrape novels from the web and plot word frequency distributions; You will gain experience with Python packages requests, BeautifulSoup and nltk.
101
101
python
+2

Hierarchical indices, groupby and pandas

In this tutorial, you’ll learn about multi-indices for pandas DataFrames and how they arise naturally from groupby operations on real-world data sets.
54
54