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!
128
128
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, ...!
98
98
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.
59
59
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
must read
data manipulation
+2

Groupby, split-apply-combine and pandas

In this tutorial, you'll learn how to use the pandas groupby operation, which draws from the well-known split-apply-combine strategy, on Netflix movie data.
100
100
python
+1

Poker Probability and Statistics with Python

Tackle probability and statistics in Python: learn more about combinations and permutations, dependent and independent events, and expected value.
61
61
python
+2

Graph Optimization with NetworkX in Python

This NetworkX tutorial will show you how to do graph optimization in Python by solving the Chinese Postman Problem in Python.
63
63
must read
machine learning
+4

Detecting Fake News with Scikit-Learn

This scikit-learn tutorial will walk you through building a fake news classifier with the help of Bayesian models.
must read
machine learning
+4
84
84
python
+1

Python Seaborn Tutorial For Beginners

This Seaborn tutorial introduces you to the basics of statistical data visualization
106
106
machine learning
+3

Apache Spark Tutorial: ML with PySpark

Apache Spark tutorial introduces you to big data processing, analysis and ML with PySpark.
73
73
python
+2

Scikit-Learn Tutorial: Baseball Analytics Pt 2

A Scikit-Learn tutorial to using logistic regression and random forest models to predict which baseball players will be voted into the Hall of Fame
27
27
r programming
+1

The data.table R Package Cheat Sheet

The data.table cheat sheet helps you master the syntax of this R package, and helps you to do data manipulations.
27
27
python
+1

5 Tips To Write Idiomatic Pandas Code

This tutorial covers 5 ways in which you can easily write pandorable or more idiomatic Pandas code.
24
24