In this medium article, I’m going to explain the basics concepts behind Keras, Transfer Learning and Multilayer Convolutional Neural Network. I’ll be introducing an interface that sits on top of TensorFlow, and allows us to draw on the power of TensorFlow with far more concise code.

That’s right. In this medium article, we’ll be building a deep neural network using a new set of tools. We’ll still have TensorFlow under the hood, but with an interface that makes testing and prototyping much faster.

Deep Learning Framework

Deep neural networks have been a big focus of work in Autonomous Driving. We’re exploring whether we can get a car to drive itself, using only deep neural networks and nothing else. Sometimes we call that behavioral cloning because we’re training the network that clone human driving behavior. Well, sometimes it’s called end-to-end learning because the network is learning to predict the correct steering angle and speed, using only the inputs from the sensors. Deep learning isn’t the only approach to building a self-driving car. For a number of years, people have been working on a more traditional sort of** robotics approach. **So, why go with deep learning over robotics approach?

#data-science #deep-learning #artificial-intelligence #self-driving-cars #machine-learning