The Anaconda Blog

Enterprise Data Science
Machine Learning in Healthcare: 5 Use Cases that Improve Patient Outcomes

Machine learning is accelerating the pace of scientific discovery across fields, and medicine is no exception. From language processing tools that accelerate research to predictive algorithms that alert medical staff of an impending heart attack,…

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Enterprise Data Science
Enterprises Need to Think Differently about Data Science. Here’s How.

Companies that are data science literate make and communicate decisions on the basis of real data models, and not merely instinct or tradition. They welcome new data science technologies as opportunities for potential innovation, rather…

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Enterprise Data Science
4 Machine Learning Use Cases in the Automotive Sector

From parts suppliers to vehicle manufacturers, service providers to rental car companies, the automotive and related mobility industries stand to gain significantly from implementing machine learning at scale. We see the big automakers investing in…

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Enterprise Data Science
Getting Started with Machine Learning in the Enterprise

Machine learning (ML) is a subset of artificial intelligence (AI) in which data scientists use algorithms and statistical  models to predict outcomes and/or perform specific tasks. ML models can automatically “learn from” data sets to…

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Enterprise Data Science
4 Ways Financial Firms Put Machine Learning to Work

Several industry giants in the finance sector are well on their way to implementing machine learning technology that improves operations and guides strategy in multiple departments. So far, machine learning algorithms are being used in…

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Enterprise Data Science
The Human Element in AI

The over 45 speakers at AnacondaCON 2019 delved into how machine learning, artificial intelligence, enterprise, and open source communities are accomplishing great things with data — from optimizing urban farming to identifying the elements in…

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Enterprise Data Science
Deriving Business Value from Data Science Deployments

One of the biggest challenges facing organizations trying to derive value from data science and machine learning is deployment. In this post, we’ll take a look at three common approaches to deploying data science projects,…

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Enterprise Data Science
Bringing Dataframe Acceleration to the GPU with RAPIDS Open-Source Software from NVIDIA

Today we are excited to talk about the RAPIDS GPU dataframe release along with our partners in this effort: NVIDIA, BlazingDB, and Quansight. RAPIDS is the culmination of 18 months of open source development to…

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Enterprise Data Science
Preparing Your Organization for Implementing an AI Platform

You already know that implementing an enterprise-ready AI enablement platform is key to executing your organization’s AI and machine learning initiatives. But can software so complex really be easy to implement? How can you avoid…

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Enterprise Data Science
AI Opportunities for Financial Services Companies

By Michael Grant AI is undeniably a hot topic right now, and financial services companies are not immune to the hype. And in truth, they shouldn’t be: the applications of advanced AI within financial services…

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Enterprise Data Science
AI Enablement Platform for Teams at Scale—Accelerate Your AI/ML Productivity with Anaconda Enterprise and Cisco UCS

By Daniel Rodriguez Anaconda Enterprise is a software platform for developing, governing, and automating data science and machine learning pipelines from laptop to production. It is the de-facto standard for data science and machine learning,…

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Enterprise Data Science
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 in hearing about the inspiring and innovative ways our customers use our products…

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