New deep learning model brings image segmentation to edge devices


AttendSeg is a new neural network architecture from DarwinAI designed to perform image segmentation on low-power/capacity computing devices.Read More

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How machine learning enhances customer segmentation

One of the key challenges that marketing teams must solve is allocating their resources in a way that minimizes “cost per acquisition” (CPA) and increases return on investment. This is possible through segmentation, the process of dividing customers into different groups based on their behavior or characteristics. Customer segmentation can help reduce waste in marketing campaigns. If you know which customers are similar to each other, you’ll be better positioned to target your campaigns at the right people. Customer segmentation can also help in other marketing tasks such as product recommendations, pricing, and up-selling strategies. Customer segmentation was previously a… This story continues at The Next Web

Deep learning models DON’T need to be black boxes — here’s how

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are often a mystery — even to their creators. This is a challenge that has been troubling the artificial intelligence community since deep learning started to become popular in the early 2010s. In tandem with the expansion of deep learning in various domains and applications, there has been a growing interest in developing techniques that try to explain neural networks by examining their results and learned parameters. But these explanations are often erroneous and misleading, and… This story continues at The Next Web

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