What is Deep Learning?

What is Deep Learning

Are you stupefied by the wonders of science? Do the machines made by humans blow your mind with their innate potential and the vast amount of functions they perform?  Then here is another aspect of machine learning that will definitely stun. Deep learning is a concept that is a sub-discipline of machine learning where the computer learns to replicate the functioning of the human mind and learn by example. Studying by example comes easily to humans and because of the expanding scope of deep learning, machines are getting to use it on their functioning. The advantages of this technology are numerous and with time are expanding to become more diverse. For a person become familiar with the term deep learning, the first vital question that arises is what is deep learning. Being used in almost every industry, it is imperative to have an idea of what it is. This blog is an attempt that seeks to answer the question with other relevant information related to its applications, courses offered in it and scope of the field.

What is Deep Learning?

Have you ever stopped to wonder about automated driving? It has been made possible because of deep learning.  Deep learning is a technology that involves a computer to have the ability to distinctly understand commands from images or sounds and use them in its functioning. The technology drives on computer learning from the examples fed into it. Algorithms are used to instill the neural networks of the computer the ability to identify between situations and perform the required function with high accuracy, efficiency and no time lapse. The nuances of deep learning can be complex and require a fuller understanding of artificial intelligence, computer systems and other essential principles of technology.

Must Read: MS in Machine Learning

How Does it Work?

As a subset of Machine Learning, Deep Learning is wholly based on learning, enhancing and growing on its own by assessing and examining algorithms. Machine Learning focuses more on simpler concepts and processes while artificial neural networks are used in Deep Learning to design it similar to human-like intelligence. Here is how it really works:

  • The neural networks in Deep Learning are quite like neurons that make up a human brain and the nodes under these networks are in individual layers which are further connected with adjacent layers.
  • This way, the network is deeper with a larger number of layers. So, like a single neuron gets innumerable signals from other neurons in the brain, an artificial neural network also has signals travelling across nodes and then corresponding weights are assignment.
  • A node with a heavier weight pushes more effect on the next layer of nodes and the final layer puts together all the weighted inputs to finally produce an output.
  • Thus, deep learning systems need to have strong hardware because of the massive amount of data that needs to be processed and the complex math calculations that will be needed.
  • Training computation takes many weeks to get to the final output and also require vast amounts of data to provide accurate results. These systems usually begin with basic-level results and then learn on their own to finally reach as accurate results as possible.

Deep Learning vs Machine Learning

Simply put, Deep Learning is a subset of Machine Learning. Here are the key differences between Deep Learning vs Machine Learning:

  • In Deep Learning, we create neural networks to train an algorithm for a certain task like face recognition, self-driving, etc. On the other hand, Machine Learning encompasses everything from deep learning to reinforcement learning and from computer vision to natural language processing.
  • Machine Learning is mostly focused on rule-based methods and every algorithm needs guidance in some way or another to carry on tasks while in Deep Learning model, once trained, has its own way of computing similar to having its own brain through which it learns on its own.
  • Deep Learning is more closer to human-like artificial intelligence while Machine Learning takes an informed decision on what it has learned while deep learning goes beyond decisions and learns further on its own.

The perfect example of Deep Learning is Ultron in Marvel’s Avengers: Age of Ultron as it develops its own consciousness or Terminator which is quite similar to deep learning.

On the other hand, Alan Turing formulated the cryptoanalysis of enigma inventing the cryptoanalytical Bombe Machine to crack German Enigmamachine-encrypted codes which is one of the best and earliest examples of Machine Learning algorithm in the world.

Applications & Examples

Understanding what is deep learning can be futile if its multifarious applications aren’t understood. With a world immensely dependent on technology, this concept is making it more convenient for technology to perform functions that would have otherwise needed more time. Its application can be understood at various levels but enlisted below are some of the crucial ones are as follows:

  • It is used to perform activities with the state of the art efficiency that beats human performance with its accuracy
  • It is used in automated driving to automatically identify stop signs, traffic lights and any other object on the path of driving
  • It is used in aerospace and for defence because of its ability to detect far off objects without any limitations and identify spaces as safe or unsafe on the basis of its findings
  • Another important application of deep learning is in medical research where it is used to detect cancerous cells in the body of an individual.
  • Additionally, it is used in electronics like hearing aids where it can detect the sound stimulus to enhance the listening capability of an individual.

Check out some amazing Applications of Artificial Intelligence!

Courses and Universities

Knowing about what is deep learning is the first step towards working in the field. For students wishing to pursue it as a profession, the most important step is to decide the course they would like to pursue and the university offering the course. Deep Learning is a specialised field of technology and artificial intelligence and therefore is often encompassed in degrees of the two fields. Choosing the right course and university is a crucial step towards establishing a successful career. Organized below are some of the valued courses in deep learning and associated fields offered by some of the esteemed universities of the world.

Course Level University
Bachelor’s in Information Technology Bachelor’s Monash University
Bachelor’s in Information and Data Science Bachelor’s University of Bedfordshire
Bachelor’s in Information Technology and Law Bachelor’s Liverpool Hope University
Master’s in Data Science and Artificial Intelligence Master’s European Business University
Master’s in Neural Networks and Neural Computers Master’s Moscow Institute of Physics and Technology (MIPT)
Master’s in Information Security Master’s University of Winchester
Master’s in Multidisciplinary Innovation Master’s Northumbria University
Master’s in Digital Control Systems Master’s ITMO University St. Petersburg

Also Read: Masters in Artificial Intelligence: Courses and Universities

Career Scope

An important step after knowing about what is deep learning is to gather information about the career scope in the field. An up and coming technology, there are virtually limitless options to choose from in this field. Honing some of the skills in machine learning can help in landing a dream job in the professional world. Listed below are some of the major profiles a person can work as with a degree in deep learning.

  • Research Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Data Scientist
  • Full-Stack Developer
  • Software Architect

This blog gives a minuscule understanding of the vast field of deep learning. Are you planning to enroll in the most venerated universities in the world for a degree in deep learning? Experts at Leverage Edu will help you with the admission process and review your application. Register today for an e-meeting and let your ideas take over the world!

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  1. You have explained the deep learning concept very nicely and differentiate in a best way with machine learning. I like very much the career part of the blog. Thank you for valuable information.

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