Your data nerd best friends
Despite its promise, machine learning can be downright daunting. Best efforts can be quickly undermined by uncertainty about a rapidly changing technical landscape, bewilderment on how best to build and organize teams, and difficulty separating hype from reality.
Free up executives and data science teams to focus on the future of the business with a virtual dedicated research staff that continually monitors the latest techniques and industry best practices, determining how best to apply them to your difficult business problems.
Cloudera Fast Forward Labs Research focuses on emerging trends that are still changing due to algorithmic breakthrough, hardware breakthrough, technological commoditization, and data availability. Accompanying the reports are working prototypes that exhibit the capabilities of the algorithm and offer detailed technical advice on its practical application.
What's in a research subscription?
A Cloudera Fast Forward Labs research subscription opens up new use cases for your data and delivers a vital head start through:
- Quarterly reports, which focus on different emerging data and machine learning-enabled capabilities that will be relevant in a six-month to two-year timeframe.
- A prototype demonstrating its application
- Access to all previously published research reports and prototypes
- A weekly newsletter with updates on new research and developments in the field
- Four hours per month of remote consulting to support your data and machine learning efforts
Latest research
Transfer learning for NLP
Natural language processing (NLP) technologies can translate language, answer questions, and generate human-like text, but the underlying deep learning techniques require costly datasets, infrastructure, and expertise. In this report, we show how to use transfer learning to adapt existing models to any NLP application, making it easier to build high-performance NLP systems.
Deep learning for image analysis - 2019 edition
Convolutional neural networks (CNNs or ConvNets) excel at learning meaningful representations of features and concepts within images, making CNNs valuable for solving problems in multiple domains, from medical imaging to manufacturing. In this report, we show how to select the right deep learning models for image analysis tasks and techniques for debugging deep learning models.
Cloudera machine learning advisory services
Understand where to focus valuable resources, how to implement effective practices, and how to expedite moving from development to production while avoiding technical dead ends.
The Fast Forward Labs Blog
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Automating Weak SupervisionWhat is weak supervision?...
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Theories of (machine) learning should shape horizon scanning - not just applicationAnd no, not this kind of horizon… (image credit)...
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