New Research eBook – Winning at Data Science: How Teamwork Leads to Victory
As we’re catching our breath from the whirlwind that was AnacondaCON, we’re excited to reveal the findings of a study we have been working on…
Five Organizations Successfully Fueling Innovation with Data Science
Data science innovation requires availability, transparency and interoperability. But what does that mean in practice? At Anaconda, it means providing da…
Here Comes The Data Science—And It’s All Right
Did you know that 94 percent of enterprises are using open source technologies for Data Science, and 96 percent of company executives say Data Science is…
Anaconda Rides its Way into Gartner’s Hype Cycle
If you’re an Anaconda user and/or frequent reader of our blog, then you know how passionate we are about empowering our community (and future community!) with all the resources needed to bring data science to life. And while it will never stop us from tooting the data science horn, it’s always nice to know we […]
Parallel Python with Numba and ParallelAccelerator
With CPU core counts on the rise, Python developers and data scientists often struggle to take advantage of all of the computing power available to them….
Using Anaconda and H2O to Supercharge your Machine Learning and Predictive Analytics
Anaconda integrates with many different providers and platforms to give you access to the data science libraries you love with the tools you use, includi…
Using Anaconda to Embrace Python 3 And Support Python 2
The data science community received a special delivery in December with the release of Python 3.6. At the time, I had a conversation with The New Stack to discuss what’s new with this release, and why we at Continuum see 2017 as the year that Python 3 is beginning to dominate the data science landscape, […]
Conda’s New Noarch Packages
Beginning with conda version 4.3 and conda-build 2.1, two new types of noarch packages are supported. Noarch Python packages cut down on the overhead of …
Reinforcing Open Data Science Foundations with conda 4.3 Release
At Continuum Analytics, we talk a lot about Open Data Science—this new world order of analytics that is rapidly accelerating the pace of innovation…
Productionizing and Deploying Data Science Projects
An end-to-end data science workflow includes stages for data preparation, exploratory analysis, predictive modeling, and sharing/dissemination of the results. At the final stages of the workflow, or even during intermediate stages, data scientists within an organization need to be able to deploy and share the results of their work for other users (both internal analysts […]