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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November 07, 2019
07
Nov'19
Booz Allen releases Modzy AI platform and marketplace
Booz Allen Hamilton introduced an AI platform and marketplace made for uploading, deploying and managing AI models across a scalable environment.
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November 04, 2019
04
Nov'19
Microsoft launches Azure Synapse Analytics for the cloud
New Microsoft Azure analytics service provides cloud BI and machine learning, enabling users to do analytics on data in various sources, including data warehouses and data lakes.
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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.
Big data and machine learning Get Started
Bring yourself up to speed with our introductory content
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UX defines chasm between explainable vs. interpretable AI
From deep learning to simple code, all algorithms should be transparent. The frameworks of AI interpretability and explainability aim to make machine learning understandable to humans. Continue Reading
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Data visualization process yields 360 AI-driven analytics view
Data visualization tools find increasing uses as part of AI processes to explore data in the initial stages of model development and make outputs easier to digest. Continue Reading
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Big data
Big data is a combination of structured, semistructured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications. 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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How to optimize hyperparameter tuning for machine learning models
Adding hyperparameters tuning to your organization's research and design modelling process enables use case, region or data-specific model specifications. Continue Reading
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How stock market prediction using AI impacts the trading floor
Robo-advisors and stock monitoring bots are changing the way traders and investors take on the stock market. Continue Reading
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How Getty Images reduces bias in AI algorithms to avoid harm
In applications from internal job recruiting to law enforcement technology, AI bias is a widespread issue. Here's what enterprises can do to reduce bias in training and deployment. Continue Reading
Manage Big data and machine learning
Learn to apply best practices and optimize your operations.
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Machine learning ops to lead AI in 2020
The increased usage of pre-trained models, machine learning ops coming to the fore and increased transparency are all poised to lead the new year in AI. Continue Reading
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Data visualization in machine learning boosts data scientist analytics
Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models. Continue Reading
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Using small data sets for machine learning models sees growth
While massive data sets allow for easy training, developers are using new techniques to mine and transfer data that allows for training on limited labeled information. 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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How to create a data set for machine learning with limited data
A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
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Machine learning for data storage optimizes data analysis
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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