Big data and machine learning
Big data and machine learning is a powerful pair for data-driven enterprises. Data collection and storage using big data frameworks, data integration and data preparation can be difficult for even the most experienced data scientists. Get expert insights and best practices for working with big data and machine learning projects.
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Big data and machine learning News
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August 07, 2019
07
Aug'19
HPE acquires MapR storage layer for AI, containers
MapR storage technology gets a new lease on life from HPE, which plans to integrate the AI data management features with recently acquired BlueData container-as-a-service platform.
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June 20, 2019
20
Jun'19
New Amax servers aim to accelerate AI and ML workflows
The Amax BrainMax Series servers feature the latest Nvidia RTX GPU accelerator cards for intensive GPU and AI applications and deep learning initiatives.
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April 08, 2019
08
Apr'19
Google's BigQuery ML needs big changes to compete
On the eve of Google Cloud Next '19, experts assess the impact of Google's BigQuery ML since its release and their hopes for the automated machine learning tool's future.
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April 02, 2019
02
Apr'19
$1 billion SAS AI investment recharges vendor's mission
SAS' new AI initiative includes a $1 billion investment and partnership with AI chip vendor Nvidia. The goal is to bring advanced AI tech to end users.
Big data and machine learning Get Started
Bring yourself up to speed with our introductory content
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big data
Big data is an evolving term that describes a large volume of structured, semi-structured and unstructured data that has the potential to be mined for information and used in machine learning projects and other advanced analytics applications. Continue Reading
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Machine learning platform architecture demands deep analysis
This handbook offers advice on choosing machine learning platforms and using them to get accurate and meaningful information from analytics applications. Continue Reading
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Data science and machine learning platforms advance analytics
Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used. Continue Reading
Evaluate Big data and machine learning Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Machine learning for data analytics can solve big data storage issues
Discover how AI and machine learning -- with support from major vendors and technologies like Lambda architecture, FPGAs and containers -- address big data analytics challenges. Continue Reading
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Machine learning for data storage optimizes data analysis
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More to machine learning platforms than meets the AI
To reach full analytics potential, machine learning platforms powered by AI must provide scalability, handle multiple models, integrate with data sources and be cloud-friendly. Continue Reading
Manage Big data and machine learning
Learn to apply best practices and optimize your operations.
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Cloud cost implications of the 5 V's of big data
Moving analytics to the cloud opens a lot doors for users, but only if they keep costs in check and understand the 5 V's of big data -- volume, variety, velocity, veracity and value. Continue Reading
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AI and big data go perfectly together -- sometimes
The combination of big data and AI tools enables new forms of analytics and automation, but use of the technologies in enterprise applications is still evolving. Continue Reading
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How to improve candidate matching with AI in HR recruitment
AI in HR recruitment can source talent externally but can also be used to improve internal projects. AI platforms can match qualified existing employees to potential open projects. Continue Reading
Problem Solve Big data and machine learning Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Mastercard CTO talks AI for fraud prevention, data and hiring
Kush Saxena, CTO of Mastercard, answers three questions about his company's use of AI fraud prevention technology, machine learning and driving commercial value from data at the MIT CIO Symposium. Continue Reading
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Clean data for machine learning is key to successful AI
Many enterprises think their AI projects should start with massive amounts of data. But clean data for machine learning should be their first step toward AI. Continue Reading
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Convert unstructured data to structured data with machine learning
With access to powerful compute power and advances in machine learning, unstructured data is becoming easier and cheaper for businesses to turn into usable sources of insight. Continue Reading