Deep Dive into Artificial Neural Networks - A detailed Guide
By Kamal Jacob
The machine is not like a human brain, nor is the human brain is like a machine. We can think of a simple machine as a set of algorithms that convert the input to output, hence the same input will always lead to the same output. On the other hand, with the help of neurons, the human brain has an inevitable characteristic of creating transient states in between the sensory organs and the decision-making unit (brain) that bring out a factor of randomness, which we call, "Creativity" or "Intelligence". That’s the reason, to make a machine learning in a more sophisticated manner, in ANN or rather all ML algorithms, transient states are built.
The objective of this guide is to give you detailed knowledge about ANN in parallel to the functionality of the human brain. Along with that, you'll also learn:
- HOW DO ARTIFICIAL NEURAL NETWORKS WORK?
- TYPES OF ANN
- ANN ARCHITECTURE TYPES
- ANN EXAMPLEs
- APPLICATIONS OF ANN
- NEURAL NETWORK & DEEP LEARNING
- USE CASE: IMAGE CLASSIFICATION USING ANN
- (PYTHON IMPLEMENTATION)
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