Tutorials

must read
pandas
+1

Pandas Tutorial: Importing Data with read_csv()

Importing data is the first step in any data science project. Learn why today's data scientists prefer pandas' read_csv() function to do this.
35
35
deep learning
+2

Demystifying Generative Adversarial Nets (GANs)

Learn what Generative Adversarial Networks are without going into the details of the math and code a simple GAN that can create digits!
31
31
r programming
+1

Long to Wide Data in R

Learn why you would transform your data from a long to a wide format and vice versa and explore how to do this in R with melt() and dcast()!
17
17
deep learning
+2

Stock Market Predictions with LSTM in Python

Discover Long Short-Term Memory (LSTM) networks in Python and how you can use them to make stock market predictions!
61
61
must read
python
+1

Markov Chains in Python: Beginner Tutorial

Learn about Markov Chains, their properties, transition matrices, and implement one yourself in Python!
64
64
must read
statistical modeling
+1

Survival Analysis in R For Beginners

In this tutorial, you'll learn about the statistical concepts behind survival analysis and you'll implement a real-world application of these methods in R.
must read
statistical modeling
+1
55
55
statistical modeling
+1

GFLASSO: Graph-Guided Fused LASSO in R

Explore graph-structured multi-task regression with the GFLASSO R package with this tutorial!
8
8
webscraping
+1

Absolute and Weighted Frequency of Words in Text

In this tutorial, you'll learn about absolute and weighted word frequency in text mining and how to calculate it with defaultdict and pandas DataFrames.
10
10
must read
machine learning

A Beginner's Guide to Object Detection

Explore the key concepts in object detection and learn how they are implemented in SSD and Faster RCNN, which are available in the Tensorflow Detection API.
must read
machine learning
43
43
r programming
+1

Network Analysis in R: Centrality Measures

Explore the definition of centrality, learn what different types of centrality measures exist in network analysis and pick the best one for a given network!
42
42
importing & cleaning data
+1

Reading and Writing Files in Python Tutorial

Learn how to open, read and write data into flat files, such as JSON and text files, as well as binary files in Python with the io and os modules.
importing & cleaning data
+1
24
24
must read
r programming
+1

Logistic Regression in R Tutorial

Discover all about logistic regression: how it differs from linear regression, how to fit and evaluate these models it in R with the glm() function and more!
must read
r programming
+1
49
49
must read
tidyverse
+4

Getting Started with the Tidyverse: Tutorial

Start analyzing titanic data with R and the tidyverse: learn how to filter, arrange, summarise, mutate and visualize your data with dplyr and ggplot2!
24
24
importing & cleaning data
+1

Pickle in Python: Object Serialization

Discover the Python pickle module: learn about serialization, when (not) to use it, how to compress pickled objects, multiprocessing, and much more!
importing & cleaning data
+1
34
34
keras
+1

Implementing Autoencoders in Keras: Tutorial

In this tutorial, you'll learn more about autoencoders and how to build convolutional and denoising autoencoders with the notMNIST dataset in Keras.
33
33