Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...

Learn how recommendation algorithms, streaming recommendations, and social media algorithms use content recommendation systems to deliver personalized recommendations. Pixabay, TungArt7 From movie ...

Katie has a PhD in maths, specializing in the intersection of dynamical systems and number theory. She reports on topics from maths and history to society and animals. Katie has a PhD in maths, ...

If you’ve ever grabbed your phone “for just five minutes” and somehow found yourself still scrolling through TikTok, Instagram Reels or YouTube Shorts an hour later, you can relate. Many people assume ...

Artificial Intelligence with Chinese Characteristics revolves around its primary logistical bottleneck and one of China's most enticing exports - green energy. Since taking office in 2013, Chinese ...

LinkedIn support accidentally revealed its algorithm: it tracks "viewer tolerance," reducing visibility for authors whose posts are consistently ignored. To succeed, diversify content types weekly, ...

President Trump said Chinese leader Xi Jinping approved a deal for a group of American investors to take control of TikTok’s U.S. operations. Photo: Mandel Ngan/AFP/Getty Images The future of TikTok ...

Algorithms, which are just sets of instructions expressed in code, are harder to restrict than physical goods. But governments, including the U.S., have long tried to prevent their export. The ...

A subtle but profound transformation is underway – one that’s redefining how people search and what content Google considers worth finding. We’ve all seen the headlines and the data: younger users are ...

This deep dive covers the full mathematical derivation of softmax gradients for multi-class classification. #Backpropagation #Softmax #NeuralNetworkMath #MachineLearning #DeepLearning #MLTutorial #AI ...

Abstract: This study proposes theories and applications of probabilistic divergences to neural network training. This theory generalizes the cross-entropy method for backpropagation to the ...