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Deep Learning Applications

Milly Gawde

2 years ago

Deep Learning Applications | insideAIML
Table of Contents
  • Introduction
  • Applications of Deep Learning
  • Computer Vision

Introduction

          Today most of the artificial intelligence problems are solved using Deep learning techniques. It provides better results than traditional Machine learning approaches. As sometimes machine learning does not perform better as the size and complexity of the data increases. Here Deep learning plays an important role and provides better results.

Applications of Deep Learning

Some of the most popular applications of Deep learning are:
  • Computer vision
  • Language translation
  • Image captioning
  • Audio transcription
  • Molecular biology
  • Speech recognition
  • Natural language processing
  • Self-driving cars
  • Brain tumour detection
  • Real-time speech translation
  • Music composition
  • Automatic game playing
There are many more applications of deep learning techniques in the field of Artificial Intelligence.
Deep learning techniques is the next big leap after machine learning with a more advanced implementation. Currently, it is heading towards becoming an industry standard bringing a strong promise of being a game changer when dealing with raw unstructured data and very large amount of data.
Deep learning is currently one of the best solution providers for a wide range of real-world problems. Developers are building AI programs that, instead of using previously given rules, learn from examples to solve complicated tasks and gives the most accurate results.
Deep learning is being used by many data scientists, where Deep neural networks are delivering results that are ever more accurate as compared to others techniques.
The idea behind deep neural networks is to develop deep neural networks by increasing the number of training layers for different hidden layers present in the network. Machine learns more about the data until it is as accurate as possible. Many data scientist and developers use deep learning techniques to implement complex machine learning tasks, and also to train AI networks to have high levels of perceptual recognition with desired results.
The most popular application of Deep learning is Computer vision.
Application of Deep Learning | insideAIML

Computer Vision

  • Image Classification
  • Image Classification with Localization
  • Object Detection
  • Object Segmentation
  • Image Style Transfer
  • Image Colorization
  • Image Reconstruction
  • Image Super-Resolution
  • Image Synthesis
Here one of the main tasks is achieved is the image the classification was given input images are classified into different classes such as cat, dog, male, female etc.
It’s a very difficult task for a machine to learn how to classify different images. As we humans learn how to do this task very early in our lives and have these skills of quickly recognizing patterns, generalizing from prior knowledge, and adapting to different image environments. Deep Learning also shows the promising result to classify the different images.
So, Deep Learning has a wide application in the real world problems. 
I hope you enjoyed reading this article and finally, you came to know about Deep Learning applications.
      
For more such blogs/courses on data science, machine learning, artificial intelligence and emerging new technologies do visit us at InsideAIML.
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