What is Deep Learning & How Do I Get Started

What is Deep Learning?

In his popular 1930s and 40s science fiction series, Isaac Asimov coined the phrase “positronic brain”. His books imagined a world where robots used futuristic-sounding “positrons” (a newly discovered particle at the time) as the basis for an artificial intelligence that could mimic human actions. Unfortunately, positrons didn’t make a great basis for neural networks, but now, through artificial intelligence and deep learning, Asimov’s larger ideas are coming to life – by some accounts, quite literally.

Deep Learning, Machine Learning, Artificial Intelligence, and Neural Networks

Deep learning, machine learning, artificial intelligence, and neural networks – a heady quartet of technologies that overlap and work together to approximate Asimov’s basic ideas. But what role do they each play in that process?

Artificial intelligence encapsulates the effort to make intelligent machines. The objective is to create devices that can carry out a diverse set of tasks that make our lives easier and more productive. Current day examples range from industrial applications, such as robotic assembly lines, to consumer products, such as self-driving cars.

Machine learning is the branch of artificial intelligence that seeks to give machines the ability to self-learn; as opposed to being limited by a specific program to do a task. Tesla’s self-driving cars provide a great example. The car comfortably navigates peak hour traffic by considering millions of variables, including its driver’s whims.

Deep learning is a subset of machine learning that deals specifically with training neural networks. Neural networks are algorithms fashioned to mimic the human brain. The intention is for the outcome of any input to be similar to that which the human brain creates. This could include responses to text, sound, and image data. And it is these neural networks that enable a machine to learn to adapt to the changing environment.

For instance, when uploading a photo to Facebook, the platform often nudges the user to tag their friends by recommending names. This function is driven by a neural network within the Facebook algorithm.

Why are Deep Learning Skills Important for My IT Career?

The dependence on machines to do our jobs is increasing every day. We are already in a world where we turn to Alexa to do things rather than press the remote. As our dependence grows, the need for more significant AI will increase. As machine inter-dependence grows, the right neural networks that recognize stimuli will be required. Deep learning, therefore, is going to be the bedrock around which the future is going to be built.

Hence, if you are looking at a career in IT that will be around for a long time, deep learning is the one subject domain you should explore and skill yourself seriously if you want to be relevant to roles that are being defined today for the future.

As a programmer today, you would possibly write pieces of code that would go into an application. Imagine tomorrow when advanced AI-driven applications will write out pieces of code based on their learning of how a particular machine is to self-adjust itself.

Who will be the person to define the architecture of the neural network that would be required for the AI application to observe, analyze and re-write code? Who will be the person to write out the neural network needed to make it happen?

The demand is growing. For example, in May 2022, LinkedIn had over 6500 jobs for deep learning roles. Another job site based out of India lists over 10,000+ jobs. Indeed the global job site indicates that the average salary for a deep learning specialist in the USA is $132,380 per year. All of these point out that deep learning is here to stay and grow.

Having the right skills in deep learning will ensure that your IT career moves in the right direction upwards with a higher salary and better growth prospects.

How Can I Build a Career in Deep Learning?

To become adept in deep learning and build a career in it, there are specific skills that you will need to acquire or already have.

Strong knowledge of Python or R

Python is the preferred programming language of AI/ML, and having this basic knowledge will help you on your career path to becoming a Deep Learning Specialist

Understand the fundamentals of Data Structures

AI/ML/DL are all based on vast amounts of data, whether text, sound or images. Understanding how to play around with these data sets will be crucial

Understanding of software development

Since you will ultimately be creating a piece of software algorithm, understanding the process of software development and having the necessary software engineering skill sets is a must

Cloud Computing Platform Knowledge

Since Machine Learning involves vast data, most AI/ML applications run over the cloud. Having a fundamental knowledge of cloud computing therefore helps

Tensor Flow

This is a popular DL framework created by Google and is now deemed one of the best libraries for implementing deep learning. With this course, you could grasp the basic beginner-level understanding of Tensor Flow.

Deep Learning Mentorships & Certifications

As you begin your journey into deep learning, it is vital to seek out more experienced professionals in this industry and gain some mentorship from them. One of the best ways to do it is to seek them out on LinkedIn. Send out a connection request to senior deep learning professionals. Do make it a point to tell them what and why you want to connect with them.

Several online platforms such as Mentor cruise and Speedy Mentors provide facilities to reach out to and engage with mentors.

While you engage with mentors, it is equally important to acquire the proper certifications. An excellent way to begin your journey into deep learning is to first understand the fundamentals of Deep Learning and practice your hands and brain at some beginner level to know what and how neural networks get strong.

Resources for a better understanding of Deep Learning

Once you have decided that Deep Learning will be the subject matter of your future career, read or watch as much as you can about the subject matter.

Quora is an excellent place to engage and read up on discussions regarding Deep Learning. Likewise, Reddit & Github are good resources to gather information. You could also subscribe to the Deep Learning Weekly newsletter.

If you like listening to Podcasts, you could tune into The TWIML AI Podcast. For an exhaustive list of resources around machine learning, AI and deep learning, we recommend that you look up Robbie Allen’s curated list.

If you would like help exploring this subject matter or guidance in finding the path best suited for your background, our learner support team can help.