Welcome. This post is part of a series of Continuum Analytics Open Notebooks showcasing our projects, products, and services.
In this Continuum Open Notebook, you’ll learn more about how Numba works and how it reduces your programming effort, and see that it achieves comparable performance to C and Cython over a range of benchmarks.
Accrual Ratios are an important index for assessing the performance and continued viability of every publicly traded company. Using Wakari, TR CONNECT, and Thomson Reuters Financial Data I calculated accrual ratios for a variety of companies and explored news events, which may correlate with strong signals in the data. You can easily download and edit the notebook used in this post into your Wakari account.
Welcome. This post is part of a series of Continuum Analytics Open Notebooks showcasing our projects, products, and services.
In this Continuum Open Notebook, you’ll see how Numba accelerates the performance of the GrowCut image segmentation window function by three orders of magnitude in two lines of Python.
We are happy to announce a new Anaconda add-on product called “MKL Optimizations”, which allows packages in Anaconda to take advantage of the Math Kernel Library (MKL) by Intel.
Last week, our Python training courses went virtual! In addition to open courses and customizable on-site courses, Continuum’s new virtual training courses are more cost effective and flexible for individuals, as well as organizations.
The GPU revolution of the past few years provides inexpensive access to hundreds of specialized computational units in a single silicon die. The challenge is efficiently accessing these and developing or adapting algorithms that can harness their power. Here, I’ll show how the NumbaPro module from Anaconda Accelerate can be used to parallelize a standard option pricing algorithm onto a GPU, giving a 14x speedup, using only a few extra lines of code.
The Boolean satisfiability problem can be solved extremely efficiently using SAT solvers. Over the past 20 years, SAT solvers have drastically improved. In the early 90’s SAT solvers could only handle a few hundred variables and clauses, whereas today problems with millions of variables and clauses can be solved quickly. Most of these advances are due to better algorithms, not due to better hardware.
As most of you probably already know, the PSF gave a Raspberry Pi to everyone attending PyCon 2013 in Santa Clara last weekend. I would like to take the opportunity to thank everyone involved for putting together the most fantastic PyCon ever. I’m always amazed to see this conference exceeding its own standards.
Yesterday we released the newest version of Anaconda, our premier Python distribution, and with it, we’ve also made a number of changes to our product offering.
Current computer architectures are quite different from what it used to be 25 years ago. Many things have changed, but probably the most dramatic difference has been the growing gap between CPU and memory speeds, also known as the memory wall.
Wakari provides a powerful set of pre-configured Python environments, but what if you need a Python module that Wakari doesn’t include by default?
I came across this image on Facebook:
I was struck by the unusual surnames (“Bok” and “Lexier”), and doubly suspicious about the “x” in the surname. The premise of this image is that the left text was created independently, and then the text on the right was created from it, using awesome anagram skills. This image would be a lot less impressive if the two paragraphs were crafted at the same time, so that they were anagrams of one another. So I wondered: is there a way to figure out if this is real or fake?
With data volumes growing, the ability to manage and analyze data sets is increasingly important to many governmental agencies. Recently, we were awarded $3 million to develop Blaze and Bokeh
Super Bowl 47 is just a few days away, and cubicle dwellers across America are gearing up for another round of their office Super Bowl Squares pool. If you’ve never participated in one,
For all the many strengths of Python, people often express frustration in finding, building, and installing third party packages. This pain can be especially acute
Several Continuum developers and I were invited to speak at the 93rd American Meteorological Society conference. I took the opportunity to learn a bit about climate science and set out to reproduce the Global Temperature Anomaly
Blaze is the next generation of NumPy, Python’s extremely popular array library. At Continuum Analytics we aim to tackle some of the hardest problems in large data analytics with
We are proud to announce that Wakari now supports IPython Notebook publishing and sharing! Wakari users can publish a notebook for public viewing, and obtain a permalink that can be shared and tweeted. Furthermore, when another Wakari user visits
In a previous post, we announced the partnership between Continuum Analytics and wise.io to bring fast and memory-efficient machine learning to data scientists and programmers. wiseRF, the implementation of the Random Forest algorithm from wise.io, is currently available on Anaconda.
In Malcom Gladwell‘s book Outliers — in which he explores “why some people succeed and others don’t” — he famously analyzes the surprising statistic that more professional hockey players, especially Canadian hockey players, are born earlier in the year. Gladwell
If you weren’t able to attend PyData NYC, or would like another opportunity to watch a talk or tutorial, you now have the chance. Conference videos are posted on Vimeo at: https://vimeo.com/channels/pydata.
Talks, tutorials, and lightning talks were among the
We are proud to introduce Wakari, our hosted Python data analysis environment.
We believe that programmers, scientists, and analysts should spend their time writing code, not working to setup a system. Data should be shareable, and analysis should be repeatable.
In addition to building great open-source and enterprise software, Continuum also consults with data science companies and organizations. One company we recently contracted with is Stipple. Many of those that attended PyData last month
This past March, over 50 people came to the PyData Workshop in Mountain View, CA at Google’s offices and over 120 people came to the evening sprint event. Last weekend, amidst the lights and bustle of midtown Manhattan, the PyData NYC
Python is a great language for writing experimental code quickly. With PyGame, one can add graphics to visualize the experiments effortlessly. I always enjoy using PyGame for rendering simple physics simulation in realtime. However, as the simulation scales, Python can
In Peter Wang’s SciPy Evangelism 101 talk he discussed “The Truth About Good Programmers.” He says good programmers are
We’ve updated the PyData NYC schedule with keynotes, tutorials, and accepted talks. We’re thrilled with the exciting lineup of workshops, hands-on tutorials, and talks about real-world uses of Python for data analysis.
*Whether your preferred *tool of choice is the legendary Swiss Army knife or the versatile Leatherman tool, everyone can agree that there is no substitute for a great tool that helps you get the job done.
Technological advancements in the collection, storage, and retrieval of data have ushered in a new era of Big Data. In this day and age, peta-scale data sets are ubiquitous in such diverse fields as medicine, finance, science, and web traffic.
In 1987 Martin H. Krieger wrote an article for the American Journal of Physics titled “The Physicist’s Toolkit”. Krieger develops the concept of a toolkit for physicists and discusses how thinking about doing
At the end of the 16th century, Tycho Brahe achieved a scientist’s dream — he received funding! As the lead principal investigator (PI)
Today, Continuum Analytics is releasing a new product, IOPro. This module provides fast reading of data into NumPy arrays. The engine is written in C, which ensures that data can be parsed as fast as it can be read from
Last week, we discussed how to spawn instances of Continuum’s Anaconda AMI for Amazon’s EC2 with StarCluster. This enables interested parties — businesses, individuals, and academics alike — to harness distributed computing with very little overhead.
In last week’s post on the 1000 Genomes Project, we used Amazon’s Web Service (AWS) Elastic Compute 2 (EC2) — an hourly pay as you go computing service — for our MapReduce computation. EC2 instances come in a variety of
At several hundred Terabytes and growing, the 1000 Genomes Project is clearly in the realm of Big Data. Earlier this year Chris Mueller gave two great presentations at PyData and [PyGotham]
How do literary detectives think? Let’s look at two of the most famous sleuths in literature, Sherlock Holmes and Hercule Poirot. Here’s Holmes’s key edict:
In the original Willy Wonka film, if you recall, Charlie attends a chemistry class taught by Mr. Turkentine. Mr. Turkentine asks Charlie what the result would be from a complicated mix of chemicals.
In the winter of 2011 Sascha Mehlhase completed construction on a 1:50 scale model of the ATLAS detector.
Over 48 hours, Sascha painstakingly designed a