The Complete Data Science Platform Buyer’s Guide
The data science and machine learning platform space is dynamic and crowded. In addition to understanding what the market has to offer, shopping for a platform means assessing the needs of your data science, IT, and leadership teams. There’s a lot to contemplate before choosing the right platform to accelerate your machine learning life cycle. […]
Why You Need Machine Learning
Here’s Why You Need a Machine Learning Platform to Stay on Top The predicted economic impact of AI is huge. It’s also a game-changer that can reshape the competitive landscape in every major industry. McKinsey predicts deep learning will generate up to $5.8 trillion in annual economic value. But, for your business to realize any […]
How do I become a data scientist?
According to LinkedIn, there has been a 37% annual growth in hiring for data scientist jobs between 2015-2019. The profession has topped their Emerging Jobs list for three years running, and the platform sees this level of rapid growth in data science roles across all industries. Businesses and organizations of all kinds now understand the […]
Getting Started with Deep Learning in the Enterprise
Deep learning (DL) is a form of artificial intelligence that utilizes neural networks and outperforms traditional machine learning in compute-intensive tasks such as image recognition and natural language processing. Until quite recently, only behemoths like Amazon or Google could afford to implement deep learning at scale. Today, most any company with a data scientist can […]
Selecting an Enterprise Platform for Python and Open Source: A Checklist for Buyers
Introduction Marc Andreessen famously opened an August 2011 blog article with this provocative sentence: “Software is eating the world.” His prediction was that software development would disrupt traditional industries. Indeed, companies like Airbnb, Netflix, and Uber emerged as just a few of many winners in the “on-demand” economy that disrupted industries like travel, entertainment, and […]
Leveraging AI for Enterprise Success: Insights for Leaders
Artificial intelligence (AI) stands at the forefront of technological evolution, offering unprecedented opportunities for enterprise organizations. AI is not just a technology or a tool—it is a pivotal cornerstone that will define the future of enterprises. Its applications transcend traditional boundaries, offering transformative solutions across various business functions. For example, over the past two years, […]
How to Implement an OSS Governance Program for Data Science, Artificial Intelligence, and Machine Learning
What’s Missing From Enterprise Data Science and Machine Learning? Security. Open-source software (OSS) is the backbone of data science and machine learning innovation. No single technology vendor can outmatch the open-source community. While OSS is generally safe, vulnerabilities creep in over time. Just like DevOps teams, data scientists need to develop processes that ensure they […]
Building Data Science Solutions with Anaconda
About this report Building Data Science Solutions with Anaconda is a comprehensive starter guide to building robust and complete models. The book covers everything you need to know about algorithm families and helps you build must-have skills such as building interpretable models and avoiding bias in data. By the end of the book, you’ll be able […]
Determine the Right DS Platform
Virtually every industry has embraced data science and machine learning as the next frontier for growth and innovation. Whether you have a full-fledged data science team building machine learning models or not, you’re probably wondering how to operationalize and scale your data science program. Our build versus buy whitepaper highlights the key considerations for evaluating […]
Enterprise Machine Learning
Creating Context for Data Scientist and Developer Collaboration n this report, we drill down into the developer and data scientist demographic from our 2019 State of Data Science survey of 5,000 users. From the data we find key differences and similarities between the two roles, including: Tool preferences Coding background Model delivery techniques In this […]