The question comes up again and again; what actually is deep learning? To understand deep learning let’s start with a simple use case to frame our explanation around.
The question comes up again and again; what actually is deep learning? To understand deep learning let’s start with a simple use case to frame our explanation around. That use case is one of a self driving car.
A self driving car is an autonomous vehicle that drives itself without any human intervention. This driving is broken down into three primary activities: see, decide, act. For example I see a red light, I decide to stop, I put on the brakes. But in this case the car is doing everything on its own. So where does deep learning come into it? Let’s focus on the “see” by explaining how deep learning works in the context of image recognition.
When you take a picture of something, your brain processes all the information that it receives from the camera and converts it into an image. Deep learning is a subfield of machine learning that focuses on computer vision and that attempts to mimic the human brain’s ability to recognise objects in images.
We can look at images in a two dimensional plane, but an object’s three dimensional shape and position in space can be just as useful. Because of this, visual recognition can be broken up into classification and localisation. Classification identifies an object, while localisation finds the position of the object in the image.
For the sake of this explanation, we’ll focus on localisation.
Here’s an example image of a dog.
Tesla CEO Elon Musk believes level 5 self-driving cars will be completed by the end of 2020. But the limits of deep learning will make it unlikely.
Foundational Concepts in the field of Deep Learning and Machine Learning. We’ll focus on TensorFlow because if one becomes a machine learning expert, these are the tools that people in the trade use everyday.
Artificial Intelligence (AI) will and is currently taking over an important role in our lives — not necessarily through intelligent robots.
Ethical AI in Self Driving Cars. How do we overcome the moral dilemma of bringing self-driving cars onto roads?
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. Introduction to Keras and the use of Transfer Learning in the development of Deep Learning architectures. Introduction to Keras & Transfer Learning for Self Driving Cars