1 / 7

Recurrent Neural Networks(RNNs) In Deep Learning

Recurrent neural networks (RNNs) are the state of the art algorithm for sequential data and are used by Apple's Siri and Google's voice search.<br>For more information, Pls visit the 1stepgrow website.<br>https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/<br>

mathi3
Download Presentation

Recurrent Neural Networks(RNNs) In Deep Learning

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Recurrent Neural Networks(RNNs) In Deep Learning https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  2. Table Of Content 1. What Is a RNNs Algorithm? 2. Why Is the RNNs Algorithm Important? 3. How Does RNNs Algorithm Work? 4. Applications Of RNNs Algorithm https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  3. What Is a RNNs Algorithm? Recurrent neural networks are the most advanced technique for sequential data and create the foundation of Google voice search and iPhone. Because it has internal storage, it is the first algorithm to recall its input, making it ideal for machine-learning issues involving sequence data. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  4. Why Is the RNNs Algorithm Important? Sequential data is where Recurrent neural networks shine the most. This can control inputs as well as output distances of any length. Recurrent neural networks process random input sequences using their internal memory. Recurrent neural networks are the most efficient way to predict the following words in a collection of phrases. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  5. How Does RNNs Algorithm Work? Recurrent neural networks operate on the declaration that each layer's result is saved and fed back into the design's input to predict that layer's result. To develop one layer of recurrent neural networks, the elements from several neural network layers are compacted. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  6. Applications Of RNNs Algorithm 1. 2. 3. 4. 5. 6. 7. 8. Analyze a call center's Problematic predictions. Machine Translation. Speech generation. Text creation and language processing. Tags for videos. Going to make up image descriptions. Description of a text. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

  7. THANK YOU! For Information,Please Visit: https://1stepgrow.com/

More Related