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How AI Can Improve Your Annotation Quality?

Smart Data Collective

One development that AI has led to is the growth of image annotation. Image annotation is the act of labeling images for AI and machine learning models. It involves human annotators using a tool to label images or tag relevant information. The resulting structured data is then used to train a machine learning algorithm.

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Data Labeling Improves Machine Learning & AI Efficiency

Smart Data Collective

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Amazon has a very good overview if you want to learn more.

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Equinix goes partner prospecting with AI

CIO

Multinational data infrastructure company Equinix has been capitalizing on machine learning (ML) since 2018, thanks to an initiative that uses ML probabilistic modeling to predict prospective customers’ likelihood of buying Equinix offerings — a program that has contributed millions of dollars in revenue since its inception.

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Tackling Bias in AI Translation: A Data Perspective

Smart Data Collective

To help you better understand what machine learning biases are, we have listed some of the biases that machine translation companies encounter that affect the performance of their translation system. Critically examining the labeling process and ensuring unbiased annotations will enhance the performance and fairness of AI translation models.

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The Future of AI: High Quality, Human Powered Data

Smart Data Collective

Human labeling and data labeling are however important aspects of the AI function as they help to identify and convert raw data into a more meaningful form for AI and machine learning to learn. Faster and Better Learning. AI and Machine Learning ensure that data trends are identified. Elimination of Human Mistakes.

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Sentiment Analysis Accuracy Explained by a Data Scientist: Part Two

Netbasequid

In this two-part series, we interviewed NetBase Quid TM Data Scientist, Michael Dukes, to help us break down precisely what sentiment analysis is, how it works, and the technological processes that differentiate “accurate” from “okay” analyses. Q: What are the problems with deep learning? Inexplicability.

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How to Conduct Deeper Market Analysis

Alpha Sense BI

To stay ahead of new trends, identify risks and opportunities, and gain competitive advantages, you need the ability to conduct deeper market analysis that goes beyond simply consuming information but that helps you make smarter decisions and build better strategies. And yet, not all market analysis is created equal.