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Year: 2020

Learning Spiral AI > Blogs > 2020
Data Annotation

Why Data Annotation Services are Important to Train AI?

  • July 4, 2020
Data Annotation provides better quality training data  Advance Data Annotation Techniques helps to improve the quality of training data in an interactive manner after human correction  Takes Less time and greater output. When it comes to machine learning and AI, no element is more essential than quality training data....
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Data Annotation

How Netflix & Amazon Prime uses Data annotation and AI

  • July 4, 2020
DATA ANNOTATION  Data annotation plays a very important role in ascertaining your AI and machine learning projects are trained with the right information to learn from. Data annotation offers the initial setup for a machine learning model to provide accurate results.  Data annotation is an indispensable stage of data...
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Data Labeling Company

All You Need to Know About Content Services

  • July 3, 2020
Content services provide automated processes that can save time and connect employees with the information they need to work most efficiently. Many business processes today involve information that comes from multiple sources, in diverse formats. Any business wanting to minimize human intervention and maximize automation needs to find the...
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Data Labeling

Data Labeling, AI & Ecommerce?

  • July 1, 2020
Data Labeling  Machines need labeled data to make the AI system, E-commerce, and the results from algorithms more accurate. Also, Machine learning needs proper datasets and model machines to learn much accurately to assist humans to achieve their goal and this is what machine learning is used for. Data...
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Data Annotation

All You Need to Know About Computer Vision

  • June 29, 2020
Computer vision abbreviated as CV is defined as a field of study that seeks to develop techniques to help computers see and understand the content of digital images such as photographs and videos. Our work in Computer Vision & Machine Learning powers innovation in the area of various sectors...
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know about nlp

All You Need to Know About NLP

  • June 29, 2020
Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data. Know-How we help in NLP projects  Our trained...
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Interesting Stats About Artificial Intelligence

10 Interesting Stats About Artificial Intelligence

  • June 25, 2020
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. We all are aware of AI and its applications in our daily life nowadays but knowing this tech deeply is something else. Machine Learning (ML) and Deep...
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Computer Vision

HOW COMPUTER VISION COMPANIES USE LABELED DATA

  • June 25, 2020
Most powerful types of AI: Computer Vision  Computer vision is a field of study that seeks to develop techniques to help computers see and understand the content of digital images such as photographs and videos. Our work in Computer Vision & Machine Learning powers innovation in areas of various...
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Data labeling

Automated Data Labeling Vs Human Empowered Data Labeling

  • June 24, 2020
What is labeled data? Under machine learning, if you have labeled data, that means your data is properly structured or annotated, to teach your machine learning model to predict, understand, and take decisions. In general, data labeling means tasks that include data tagging, annotation, moderation, categorization, transcription, or processing....
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Data Annotation

Learning Spiral Becoming The Expert in Lidar Annotation

  • June 23, 2020
LIDAR Annotation and Labeling  LIDAR stands for LIght Detection and Ranging. It is a land surveying method that uses remote sensing technology emitting light that travels around the object and back to the receiver creating points every time it hits the object building a 3D map of the entire...
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