Deep Learning: Three Things You need to know

A machine learning technique, Deep Learning teaches computer systems to perform what humans can do naturally. It is the main technology behind driverless cars that enables them to recognise a start or stop sign or distinguish between a lamppost and pedestrian. Deep learning is also the main voice control in consumer devices like phones, TVs, and hands-free speakers.

Deep learning has been in the news lately and all for good reasons. It has made it possible to achieve results that were unlikely before.

More about Deep Learning                                                                                         

·        Deep learning models are often referred to as deep neural networks as they generally use neural network architectures.

·        The meaning of deep means the number of hidden layers in a neural network. Traditionally, neural networks contained only 2-3 layers, but now they can have as many as 150 hidden layers.

Why Deep Learning Matters?     

Deep learning’s work is to provide accuracy. It takes accuracy to higher levels than before. It offers excellent consumer experience by meeting their expectations. Besides, deep learning is crucial for applications like driverless cars.

In recent times, deep learning has outperformed humans in several tasks, such as classifying objects in images.

The following are two reasons why deep learning has become useful in recent times:

1.      It requires a large amount of labelled data. For instance, if we talk about a driverless car, it requires millions of images and videos of cars, pedestrians, road signs, etc.

2.      Deep learning requires computing power. It uses high-performing GPUs which are efficient for deep learning. When you combine it with cloud computing, it helps the development team to reduce training time and work for lesser hours.

Difference between Machine Learning & Deep Learning     

It can be said that deep learning is a form of machine learning. Machine learning has a workflow that starts with features such as extracting images manually. Then, the next feature is to categorise objects in the image.

Now with deep learning workflow, relevant features are extracted from the images automatically.

If all these interests you, then you can make a career in deep learning by enrolling yourself in a certificate course in deep learning and machine learning. With all the factors mentioned above, it is pretty evident that the course would provide a significant boost to your career.