Scalable Machine Learning with Dask—Your Questions Answered!
Building powerful machine learning models often requires more computing power than a laptop can provide. Although it’s fairly easy to provision compute instances in the cloud these days, all the computing power in the world won’t help you if your machine learning library cannot scale. Unfortunately, popular libraries like scikit-learn, XGBoost, and TensorFlow don’t offer […]
Open Source Model Management Roundup: Polyaxon, Argo, and Seldon
One of the most common questions the Anaconda Enterprise team receives is something along the lines of: “But really, how difficult is it to build this using open source tools?” This is certainly a fair question, as open source does provide a lot of functionality while offering a lower entry price than an enterprise platform. […]
Improved Security & Performance in Anaconda Distribution 5
We announced the release of Anaconda Distribution 5 back in October 2017, but we’re only now catching up with a blog post on the security and perfo…
Scalable Machine Learning in the Enterprise with Dask
You’ve been hearing the hype for years: machine learning can have a magical, transformative impact on your business, putting key insights into the …
Patching Source Code to Conda Build Recipes
If you are a developer who relies upon conda, we hope to encourage you to begin building your own packages so that your projects can be used just like all of the other packages you rely upon. The success of Anaconda rests upon the ease to search for, install, and create environments for packages while […]
Machines Learning about Humans Learning about Machines Learning
I had the great honor and pleasure of presenting the first tutorial at AnacondaCon 2018, on machine learning with scikit-learn. I spoke to a full room of…
Generate Custom Parcels for Cloudera CDH with Anaconda Enterprise 5
Introducing Dask for Scalable Machine Learning
Although Python contains several powerful libraries for machine learning, unfortunately, they don’t always scale well to large datasets. This has f…
2018 Anaconda State of Data Science Report Released
We at Anaconda greatly value our data science community and are always striving to learn more about how you are using our products and how we can improve…
Intake: Caching Data on First Read Makes Future Analysis Faster
By Mike McCarty
Intake provides easy access data sources from remote/cloud storage. However, for large files, the cost of downloading files every time d…