Recurrent Neural Networks (RNNs), Clearly Explained!!!

When you don’t always have the same amount of data, like when translating different sentences from one language to another, or making stock market predictions from different companies, Recurrent Neural Networks come to the rescue. In this StatQuest, we’ll show you how Recurrent Neural Networks work, one step at a time, and then we’ll show you their critical flaw that will lead us to understanding Long Short-Term Memory Networks. English This video has been dubbed using an artificial voice via to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out... ...or... If you’d like to support StatQuest, please consider... Patreon: ...or... YouTube Membership: ...a cool StatQuest t-shirt or sweatshirt: ...buying one or two of my songs (or go large and get a whole album!) ...or just donating to StatQuest! Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: 0:00 Awesome song and introduction 4:13 Basic anatomy of a recurrent neural network 5:59 Running data through a recurrent neural network 10:31 Shared weights and biases 11:23 The vanishing/exploding gradient problem. #StatQuest #NeuralNetworks #Deeplearning #DubbedWithAloud