Deep learning

When humans are in trouble or need to make decisions, we use our brains to come up with solutions. While researchers are still looking into how humans are naturally flared with the intellect, computers are also taking a step ahead in decision-making. With the advent of machine learning and deep learning, computers are programmed to learn and provide results on their own limited or no manual instructions. This has created hype for the technology. Today, career opportunities in machine learning and deep learning are also flourishing like never before.

Machine learning is the science of getting computers to learn and act like humans do, and improve their learning over time in an autonomous fashion, by feeding them data and information in the form of observations and real-world interactions. On the other hand, deep learning is a sub-field of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Both technologies are making breakthrough applications in many industries like healthcare, finance, manufacturing, telecom, and even entertainment. If you are someone who gets fascinated by algorithms and how statistical models work, then a career in machine learning and deep learning would be great for you. The average salary in both fields ranges from approximately US$77,562 per year for research scientists to US$135,255 per year for machine learning engineers. 

Why is it the right time to take up a job in machine learning or deep learning?

There is a big increase in the usage of machine learning and deep learning technologies. Starting from marketing campaigns and emails to mobile applications and more, everything is relying on an algorithm that is powered by the duo. But the sudden spike has a lot to do with artificial intelligence. Companies across the globe are incorporating artificial intelligence, machine learning, and deep learning into their existing systems to make them smarter and efficient. So the companies’ quest for technology has opened a lot of career options in the field. 

Machine learning professionals build programs that can modify and update machines and make them seamlessly adapt to different environments. It helps machines get things done right and faster. Henceforth, even when machines take care of all the labor-dense and time-consuming jobs, humans are the power behind them. Deep learning has gained its place in the job market after neural network dialects got popularized. As a result, deep learning engineering has numerous options for neural programming skills like building Convolutional neural network, RNN, LSTM, Batch Normalization, etc. 

Some of the famous career options in ML and DL

Machine learning engineer: Machine learning engineers’ role is quite similar to that of data scientists as both involve vast volumes of data. Machine learning engineers focus on designing self-running software for predictive model automation. 

Data engineer: Data engineers are the data professionals who prepare the ‘big data’ infrastructure to be analyzed by data scientists. They are software engineers who design, build, integrate data from various resources, and manage big data.

Artificial intelligence engineer: An artificial intelligence engineer is an individual who works with traditional machine learning techniques like natural language processing and neural networks to build models that power AI-based applications.