Exploring Deep Learning in AI with These 5 Hands-on Examples
Deep Learning in AI

A lot of conversation is happening lately about all the probabilities of machine learning to do things that humans do currently in homes, factories, warehouses, and offices. As the technology evolves at a rapid pace bringing along excitement and fears, words like deep learning, machine learning, and artificial intelligence may leave you bamboozled. We hope that this simple explanation here will help you sort out the bewilderment around deep learning.

What is deep learning?

The field of AI is basically when a machine can perform the tasks that require human intelligence. It includes machine learning, wherein machines acquire skills without the human participation and learn by experience. Deep learning essentially is a subsection of machine learning wherein drawing inspiration from the human brain, artificial neural network and algorithms learn from a large amount of data. Similar to the way we learn from experience, the algorithm of deep learning would perform a task over and over again, fine-tuning it a little every time to enhance the results.

We refer this technique as “deep learning” as neural networks have several deep layers that allow learning. Any problem that necessitates “thought” to figure out is a type of problem that deep learning can learn to solve.

The amount of data that we generate has reached a staggering limit of 2.6 quintillion bytes and it is the resource that makes deep learning conceivable. Because deep-learning algorithms require lots and lots of data to learn from, the surge in data creation is a reason that deep learning proficiencies have grown recently. Furthermore, to more data creation, deep learning algorithms have benefitted from the proliferation of AI as a service and the stronger computing power that is available today.

Deep learning enables machines to resolve complex problems even when using a data set that is inter-connected, diverse, and unstructured. The deeper the learning algorithms learn, the finer they perform.

5 practical examples of deep learning

  1. Virtual assistants

Whether it is Alexa, Siri, or Cortana, the online service providers through the virtual assistants use deep learning to help understand the human speech and language they use when they interact with them.

  1. Translations

Similarly, deep learning algorithms can potentially translate languages. This can be helpful for business people, those in governments and travelers.

  1. Prospect for autonomous drones, cars, and delivery trucks

The way an autonomous vehicle contemplates the actualities of the road and how to respond to them if it is a stop sign or another vehicle in the street is through deep learning algorithms.

  1. Service bots and chatbots

Service bots and chatbots that deliver customer service for various companies are able to answer intellectually to an ever-growing amount of aural and text questions owing to deep learning.

  1. Image colorization

Formerly transmuting color images from black-and-white was a task done diligently by human hands. But today deep learning algorithms are capable enough to use the objects and context in the images to color and recreate the black-and-white image in color. And as we all can see; the results are quite impressive and precise.