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Novelty and Outlier Detection

In my last few articles, I've looked at a number of ways machine learning can help make predictions. The basic idea is that you create a model using existing data and then ask that model to predict an outcome based on new data. more>>

V. Anton Spraul's Think Like a Programmer, Python Edition

What is programming? Sure, it consists of syntax and the assembly of code, but it is essentially a means to solve problems. To study programming, then, is to study the art of problem solving, and a new book from V. Anton Spraul, Think Like a Programmer, Python Edition, is a guide to sharpening skills in both spheres. more>>

Classifying Text

In my last few articles, I've looked at several ways one can apply machine learning, both supervised and unsupervised. This time, I want to bring your attention to a surprisingly simple—but powerful and widespread—use of machine learning, namely document classification. more>>

Zed A. Shaw's Learn Python 3 the Hard Way

Author Zed A. Shaw makes a simple promise in his Hard Way series of books from publisher Addison-Wesley Professional: "It'll be hard at first. more>>

Unsupervised Learning

In my last few articles, I've looked into machine learning and how you can build a model that describes the world in some way. All of the examples I looked at were of "supervised learning", meaning that you loaded data that already had been categorized or classified in some way, and then created a model that "learned" the ways the inputs mapped to the outputs. more>>

Testing Models

In my last few articles, I've been dipping into the waters of "machine learning"—a powerful idea that has been moving steadily into the mainstream of computing, and that has the potential to change lives in numerous ways. more>>

Pythonic Science in the Browser

In the past, if you wanted a friendly environment for doing Python programming, you would use Ipython. The Ipython project actually consists of three parts: the standard console interface, a Qt-based GUI interface and a web server interface that you can connect to with a web browser. more>>

Teaching Your Computer

As I have written in my last two articles (Machine Learning Everywhere and Preparing Data for Machine Learning), machine learning is influencing our lives in numerous ways. more>>

Preparing Data for Machine Learning

When I go to Amazon.com, the online store often recommends products I should buy. I know I'm not alone in thinking that these recommendations can be rather spooky—often they're for products I've already bought elsewhere or that I was thinking of buying. How does Amazon do it? more>>

Transitioning to Python 3

The Python language, which is not new but continues to gain momentum and users as if it were, has changed remarkably little since it first was released. I don't mean to say that Python hasn't changed; it has grown, gaining functionality and speed, and it's now a hot language in a variety of domains, from data science to test automation to education. more>>

LinkedIn's {py}gradle

To facilitate better building of Android apps, the technical team at LinkedIn has developed {py}gradle, a new powerful, flexible and reusable Python packaging system. Now available to the Open Source community, {py}gradle wraps Python code into the Gradle build automation tool so that developers can build Android apps more easily. more>>

Pandas

Serious practitioners of data science use the full scientific method, starting with a question and a hypothesis, followed by an exploration of the data to determine whether the hypothesis holds up. more>>

Analyzing Data

My first Web-related job was in 1995, developing Web applications for a number of properties at Time Warner. When I first started there, we had a handful of programmers and managers handling all of the tasks. But over time, as happens in all growing companies and organizations, we started to specialize. more>>

Geek Guide: Machine Learning with Python

I first heard the term “machine learning” a few years ago, and to be honest, I basically ignored it that time. more>>

Recipy for Science

More and more journals are demanding that the science being published be reproducible. Ideally, if you publish your code, that should be enough for someone else to reproduce the results you are claiming. But, anyone who has done any actual computational science knows that this is not true. more>>

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