Distributed Auto-ML with TPOT with Dask
By Tom Augspurger
This work is supported byAnaconda, Inc.
This post describes a recent improvement made to TPOT. TPOT is an automated machine learning l…
How PNC Financial Services Leveraged Anaconda to Enable Data Science and Machine Learning Capabilities Across the Company
As an AI software company passionate about the real-world practice of data science, machine learning, and predictive analytics, we take great pleasure i…
Anaconda Funded by Citi Ventures
By Scott Collison, CEO
Today, we’re incredibly happy to announce funding from Citi Ventures and welcome them as a new investor and partner. Follow…
Introducing Skein: Deploy Python on Apache YARN the Easy Way
By Jim Crist *This post is reprinted with permission from Jim Crist’s blog. The original post can be found here. In this post, I introduce Skein, a new tool and library for deploying applications on Apache YARN. I provide background on why this work was necessary, and demonstrate deploying a simple Python application on a YARN cluster. Introduction […]
Intake: Taking the Pain out of Data Access
By Martin Durant, Anaconda Software Engineer
We are pleased to announce the release of Intake, a simple data access layer and cataloging system.
This ar…
Faster Machine Learning—Deep Learning with GPUs
The Big Deal With GPUs
If you’ve been following data science and machine learning, you’ve probably heard the term GPU. But what exactly is a…
New Release of Anaconda Enterprise features Expanded GPU and Container Usage
Anaconda, Inc. is thrilled to announce the latest release of Anaconda Enterprise, our popular AI/ML enablement platform for teams at scale. The release o…
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…