Machine learning: A strategy to learn and understand (Chapter 4)🤖 Part 4: Neural Networks & Deep Learning.

This is the part 4: Neural Networks & Deep Learning of the series Machine learning: A strategy to learn and understand.

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Deep learning is probably the one of the most hot topic right now in tech world. Large organizations and small new startups rushing towards this emerging new field. And if you have interest in big data and automation of exiting data technologies then you should care about deep learning. Deep learning algorithms have improved over the past few decades and developers around the world have contributed to open source frameworks like TensorFlow, Theano, Keras, and Torch, all of which make it easy for people to build deep learning algorithms.

Neural networks: The definition

Neural networks are the set of algorithms and methodologies based on the working of human brain. They are designed to recognize the patterns in the available data. They interpret sensory data through a machine perception, labeling or clustering raw data. The pattern they recognize are numerical contained in vectors which all the real world data be it images, audio or text must be translated.