Wazzup Pilipinas!
NEC hardware is fully optimized to work with Hortonworks Data Platform powered by Open Enterprise Apache Hadoop
NEC and Hortonworks have strengthened their partnership to bring quality Data Management Platforms to increase efficiency in handling Big Data workloads.
NEC Philippines along with Hortonworks conducted a roundtable in Shangri-la Hotel, Makati, gathering different IT Professionals, industry executives, and industry giants in the Philippines to shed light on the importance of understanding Big Data analytics and how to utilize them for their respective industries, especially for Enterprise customers. “The NEC-Hortonworks partnership aims to provide solutions and create insight into the key factors to being competitive and driving our companies to further growth,” NEC Philippines President Elizabeth Pangan said.
“In this partnership, NEC is committed to provide the best Hadoop platform for data management processing. As part of this solution, NEC brings specialized hardware that is designed and optimized for Big Data workloads,” Pangan added. The partnership combines NEC's "Data Platform for Hadoop" with Hortonworks Data Platform to allow enterprise customers to process structured and un-structured data on a single platform. Hortonworks Data Platform is optimized with NEC’s Server hardware, such as the DX2000 which can be fully customized for a variety of Linux Operating Systems to meet the needs of the enterprise market. The roundtable was fruitful and informative as the executives listened to talks about The Art of Data Science, Getting Into the Data Driven Economy, Delivering Faster Analytics at Scale, and Hortonworks Data Platform End-to-End Solution. Both NEC and Hortonworks are committed to deliver quality support in addressing technical concerns enterprise customers might have with this Large-scale Distributed Processing Platform.
Ross is known as the Pambansang Blogger ng Pilipinas - An Information and Communication Technology (ICT) Professional by profession and a Social Media Evangelist by heart.
Annotating data for machine learning is a crucial step in the process of building effective models. As someone who has worked with machine learning models, I can attest to the importance of following best practices and avoiding common pitfalls when annotating data. That's why I found the article on Project Practical about annotating data for machine learning to be incredibly informative and helpful.
ReplyDeleteThe article provides a comprehensive overview of best practices for annotating data, including tips on how to choose the right annotation tool, how to ensure consistency in annotations, and how to handle ambiguous data. It also highlights common pitfalls to avoid, such as overfitting and underfitting, and provides guidance on how to address these issues.
One of the things I appreciated most about the article was its emphasis on the importance of quality control when annotating data. The author stresses the need for multiple annotators to review and verify each other's work, as well as the need for ongoing monitoring and refinement of annotations to ensure accuracy and consistency, and for more visit https://www.projectpractical.com/annotating-data-for-machine-learning-best-practices-and-common-pitfalls/ .
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In conclusion, if you are working with machine learning models, I highly recommend reading the article on Project Practical about annotating data for machine learning best practices and common pitfalls. It provides valuable insights and practical advice that can help improve the quality and effectiveness of your annotated data. So, don't hesitate to check it out and start improving your annotation practices today!
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ReplyDeleteOne aspect that truly stood out was the author's emphasis on the importance of high-quality data annotation. They explained how meticulous annotation ensures accurate and reliable results, enabling businesses to make informed decisions. The article also shed light on various annotation techniques, such as image and text annotation, which broadened my understanding of the subject and its practical applications.
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