How does the Artificial Neural Networks works?

                                                        


An artificial neural network is the foundation of artificial intelligence. It is used for solving problems that are impossible for humans and perform a specific task that improves self-learning capabilities. It is designed by a computing system to simulate the way the human brain analyses and are characterized by containing adaptive weights along paths between neurons that learn from observed data to upgrade the model by using different algorithms

Neural networks, a beautiful biologically-inspired programming paradigm that permits a computer to learn from observational data and overcomes many problems such as image recognition, speech recognition, and natural language processing. The human brain is abnormally complex and quite literally almost powerful computing machine known. The inner-workings of the human brain are often around the approach of neurons and the networks of neurons which is called biological neural networks

 Significant trends in neural networks:

  • Capsule Networks
  • Convolutional Neural Networks
  • Deep Reinforcement Learning
  • Lean and Augmented Learning
  • Supervised Model
  • Networks with Memory Model
  • Hybrid Learning Models

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