What are the different uses of Deep Learning

Aug 21, 2018 | 5271 Views

Deep Learning, what is it; well in layman's term it the when a machine tries to copy a human brain working. All I want to so if it copies some hope it is a smart human brain, it will for sure shut itself down if it try's copying my brain. Deep learning is present to change our perspective towards technologies. AI already has a lot of excitement around it and especially with Deep Learning. It was actually predicted that DL will have a affect to our life's, it already is having its share of impact. DL is growing faster than what most of us expect, it feeds on data, that's its fuel, and for once data is something there is plenty of in this word. Get in my belly; or get in my programming however DL likes it. Deep learning is already being used in a lot of ways around us here are some of the ways:

  • Customer experience: Be it helping customers find what they want, being at your service for 24 hours. Deep Learning is already being use in chatbots
  • Translation: Translating words, sentence or phrases from one language to another. While automatic translation is not something that is new, Deep learning has shown way better results results when it comes to translation of text or speech.
  • Adding colours to images and videos: Turning black and white images into coloured ones was a time consuming process, but with DL it can be automatically done.
  • Language recognition: When it comes to different dialect in a language DL has been able to differentiate between them very successfully. 
  • Autonomous vehicles: Companies are building these types of vehicles, while some of them are better at reading street signs others are better at recognising street patterns and people pn the road.
  • Computer vision: Deep learning has delivered super-human accuracy for image classification, object detection, image restoration and image segmentation even handwritten digits can be recognized. Deep learning using enormous neural networks is teaching machines to automate the tasks performed by human visual systems.
  • Text generation: be it generating text word by word or character by character, DL is able to learn from a collection of texts and create an appropriate reply. The model is capable of learning how to spell, punctuate, form sentences and even capture the style of the text
  • Image recognition:  the aim to recognize people and different objects in an image and understand the story behind the image. Image recognition is already being used in many industries. A great of this is the AI created that finds Waldo, which is does by scanning the whole page and matching the face of Waldo by the data provided to it how Waldo looks.
  • News filtering: When you want to filter out the negative coming to your world, advanced natural language processing and deep learning can help. News aggregators using this new technology can filter news based on sentiment, so you can create news streams that only cover the good news happening.
  • Deep learning robots: When you want to filter out the negative coming to your world, advanced natural language processing and deep learning can help. News aggregators using this new technology can filter news based on sentiment, so you can create news streams that only cover the good news happening.

There are already advancements that are going on in the field of Deep learning, new applications are coming up fast and solid and is expected to grow even more in the future.

Source: HOB