must read
git
+3

Setup a Data Science Environment on your Computer

Learn about the various options you have to setup a data science environment with Python, R, Git, and Unix Shell on your local computer.
38
38
python
+1

Reconstructing Fingerprint Images Using Deep Learning (Convolutional Autoencoder)

In this tutorial, you will learn and understand how to read jpeg format fingerprint images, reconstructing them using convolutional autoencoder.
14
14
machine learning
+6

Machine Learning and NLP using R: Topic Modeling and Music Classification

In this tutorial, you will build four models using Latent Dirichlet Allocation (LDA) and K-Means clustering machine learning algorithms.
59
59
python
+1

Predicting the Status of H-1B Visa Applications

Learn how you can predict the status of a H-1B visa application with Machine Learning in Python.
16
16
machine learning
+1

Decision Trees in R

Learn all about decision trees, a form of supervised learning used in a variety of ways to solve regression and classification problems.
48
48
must read
pandas
+2

Using Python to Power Spreadsheets in Data Science

Learn how Python can be used more effectively than Excel, with the Pandas package.
104
104
python
+1

Converting Strings to Dates as datetime Objects

Learn how to convert strings to datetime objects in Python and why doing so has become standard practice for working data scientists today.
40
40
must read
neural networks
+2

TensorBoard Tutorial

Visualize the training parameters, metrics, hyperparameters or any statistics of your neural network with TensorBoard!
must read
neural networks
+2
38
38
python

Installing Anaconda on Mac OS X

This tutorial will demonstrate how you can install Anaconda, a powerful package manager, on your Mac.
26
26
jupyter

Custom Templates for Jupyter Notebooks with Jinja2

Learn how to create custom export templates for your Jupyter Notebooks using Jinja2.
17
17
must read
spark
+1

How to Install and Use Homebrew

Discover Homebrew for data science: learn how you can use this package manager to install, update, and remove technologies such as Apache Spark and Graphviz.
16
16
python

Understanding Random Forests Classifiers in Python

Learn about Random Forests and build your own model in Python, for both classification and regression.
55
55
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.
71
71
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!
50
50
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()!
25
25