Hey Everyone, today I will explain how Google improved their Search Engine algorithm for better results with the help of deep learning.
In 2015, Google revealed that they are using a 30 layers deep Artificial Neural Network. These many layers help google to find the correct answers to Users' queries and help to find complicated searches like shape and colors.
Using Artificial Neural Network, google can learn new things constantly and will improve based on the new users' queries.
After some months, Google analyses that they are improving their search engine. Their Error rate is dropped from 23% to 8%.
After applying a deep neural network, google's search engine is improved and provides valuable and useful information on top pages.
Many applications of google use the neural network. Google is completely based on Artificial Intelligence. Deep learning helps the data scientist to solve the different use cases such as speech and image recognition.
First Practical did by Google on image recognition. On the internet, there are millions of images, google use the deep learning concept to classify the useful image.
Google Assistant speech recognition also uses the deep learning concept to learn how to understand spoken commands and questions.
Youtube is also using a deep learning concept to improve their recommendation service. After using the deep learning concept, youtube now able to understand the behavior and viewer's habits what they actually want to see on their recommendation screen.
Google's self-driving car is also using the deep learning concept for autonomous systems.
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