Deep learning Introduction

Deep learning Introduction

What is deep learning

To make Computer System intelligent (artificial intelligent) it must learn, which is done through machine learning models.

One of the model which works like human brain is called Neural network, which is reffered as Deep learning.


How does deep learning works

  • Deep Learning uses a Neural Network.
  • There are three types of layers of neurons in a neural network: the InputLayer, the Hidden Layer(s), and the Output Layer.
  • Connections between neurons are associated with a weight, depending on input value.
  • Neurons apply an Activation Function on the data to give the output to next layer.
  • Final output layer providing the output data.

Why deep learning


Traditional machine learning had low data to process, as application comprising image, text,audio & video  came up, data size was increased manyfold. So neural networks was used, and deep learning  outperformed in these applications.

Types of deep learning

1)Supervised deep learning

    a) ANN-Artificial Neural network

Email service provide to detect and delete spam from a user’s inbox; asset managers use it to forecast the direction of a company’s stock; credit rating firms use it to improve their credit scoring methods; e-commerce platforms use it to personalize recommendations to their audience.

   b)  CNN- Convulated neural network

Which  are  used in area of Computer vision eg Facebook image tagging application, driverless car.

   c)  RNN-Recurrent neural network

Which  are  used in  natural language processing eg Chatbots, social robots.

2) Unsupervised deep learning

Which is used in case of clustering problems in image, video, text, audio. eg Organizing My photo gallery  in category.

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