Go hands-on with data scientist Dr. James McCaffrey as he explains neural network dropout, a technique that can be used during training to reduce the likelihood of model overfitting.
- By James McCaffrey
- 02/26/2018
Learn how to do time series regression using a neural network, with "rolling window" data, coded from scratch, using Python.
- By James McCaffrey
- 02/02/2018
The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.
- By James McCaffrey
- 01/08/2018
The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations.
- By James McCaffrey
- 12/05/2017
Our resident data scientist explains how to train neural networks with two popular variations of the back-propagation technique: batch and online.
- By James McCaffrey
- 10/31/2017
Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining.
- By James McCaffrey
- 10/05/2017
With the help of Python and the NumPy add-on package, I'll explain how to implement back-propagation training using momentum.
- By James McCaffrey
- 08/15/2017
James McCaffrey uses cross entropy error via Python to train a neural network model for predicting a species of iris flower.
- By James McCaffrey
- 07/20/2017
You don't have to resort to writing C++ to work with popular machine learning libraries such as Microsoft's CNTK and Google's TensorFlow. Instead, we'll use some Python and NumPy to tackle the task of training neural networks.
- By James McCaffrey
- 06/15/2017
With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network.
- By James McCaffrey
- 05/24/2017
Let's explore factor analysis again, this time using the R ability to tap into OOP, but we won't use the RC model.
- By James McCaffrey
- 05/02/2017
Let's use this classical statistics technique -- and some R, of course -- to get to some of the latent variables hiding in your data.
- By James McCaffrey
- 03/16/2017
Find the patterns in your data sets using these Clustering.R script tricks.
- By James McCaffrey
- 02/01/2017
The S3 OOP model is still widely used, so let's use write S3-style OOP code via the R language.
- By James McCaffrey
- 01/10/2017
I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.
- By James McCaffrey
- 12/07/2016
The R language simplifies the creation of neural network classifiers with an add-on that lays all the groundwork.
- By James McCaffrey
- 11/10/2016
The R language can be used to perform a sign test, which is handy for comparing "before and after" data.
- By James McCaffrey
- 10/05/2016
A language that's data-intensive naturally should have a way to dig into the data effectively. Here's a look at some of the R functions for searching and sorting through it all.
- By James McCaffrey
- 09/08/2016
Vectors, lists, arrays, matrices and data frames -- a look at five of the most fundamental data structures built into R.
- By James McCaffrey
- 08/10/2016
R has limited support for mathematical permutations, but it's there. Here's what R is capable of accomplishing.
- By James McCaffrey
- 07/12/2016
It's not quite like C# or Python, but the R language's object-oriented programming capabilities are getting better with each iteration. Let's take a look at what .NET developers are able do now with OOP in R6.
- By James McCaffrey
- 06/16/2016
New to this type of analysis? It's a classic statistics technique that is still useful. Here's a technique for doing a one-way ANOVA using R.
- By James McCaffrey
- 05/04/2016
The three most common open source technologies for writing data science programs are Python, SciLab, and R. Here's how to write program-defined functions in R.
- By James McCaffrey
- 04/12/2016
R is the perfect language for creating a variety of chi-square tests, which are used to perform statistical analyses of counts of data. Here's how, with some sample code.
- By James McCaffrey
- 03/02/2016
Linear regression was easy, right? Now, let's check out t-test analysis using R.
- By James McCaffrey
- 02/02/2016