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  1. Introduction


Autonomous driving is the most active field of AI. The first autonomous car was presented in late 1989 called ALVINN, which used NN for detecting the lanes and steer based on the camera feed. Now fast forward to the present day, the autonomous vehicle (AV) still holds even greater research potential with Telsa and other companies striving towards fully AV (level 5).

The major fields of self-driving systems are perception, mapping, localization, prediction, planning and…

Photo by Markus Spiske on Unsplash

There are plenty of complex neural network examples out there to explore, but it is always better to start from the basics as it gives you more insights on the things working on rudimentary levels. So in this article, I will be using a simple deep neural network approach to predict a regression problem, which learns to predict a sine wave using the noisy signal. Moreover, there are many different methods to address this problem but I am going to implement this using TensorFlow. And this article focuses on the programming part and not the mathematics behind it.

Mathematical Description

As described…

Heilbronn Germany (Picture Credit: Srijay Kolvekar)

In artificial neural networks, activation function plays an important role in determining the output of the neuron. To make it sound more realistic, we can simply compare the activation function to the biological neurons which fire the signal to other connected neurons.


Deep Learning Enthusiast | Masters Student University of Stuttgart.

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