“A breakthrough in Machine Learning would be worth ten Microsofts.”
An era of technological advancements has made our lives full of luxuries we are living in, without realizing their presence and impact on our routine life. These technologies, which make our life easier and luxurious, are powered by Artificial Intelligence or AI.
Human nature is that it evolves and learns from past experiences. That’s what forms the base of AI. Machines are now programmed to learn from past experiences and take action accordingly. AI is the science behind developing systems or machines that can imitate humans in performing various tasks.
Machine Learning or ML is a subset of Artificial Intelligence and they are often used together. While the goal of AI is to imitate humans, ML is a procedure of training the machine to learn and recognize patterns from the given data.
Since AI forms the driving force behind economic growth, the future is impossible without AI techniques. In 2016, the Machine Learning industry was found to be worth $1.03 bn and is anticipated to reach $8.81 bn by 2022.
In recent years, ML has experienced exponential growth and the demand for machine learning professionals is shooting up regularly as the companies have now realized the power of ML. Due to growing demand and high salaries, ML engineer was found to be the best job last year, as reported by Indeed.
The average annual salary of an ML engineer is found to be $146,085 which has a growth rate of 344 percent.
With the plethora of opportunities and high salary, you now realize how great it can be to make a career in Machine Learning. You can take up the courses available online to add a certificate on your resume and try machine learning test questions to achieve the same. This will let you practice the questions before you finally appear in the exam. And it is always recommended that you take up practice tests.
Who is a Machine Learning Engineer?
Before moving to a machine learning engineer, let’s define machine learning precisely. The technique of developing systems that are capable of analyzing existing data, learn the patterns, and make decisions/predictions/classifications, or draw conclusions on similar data with negligible human intervention.
So, a machine learning engineer is clearly a programmer who can develop machines or systems that can learn and implement knowledge without specifically being guided. The goal of ML engineers is AI.
As an ML engineer, you need to guide applications through big data tools and make sure that the applications are getting the required information to grow. You can also help organizations to make informed decisions thereby improving the productivity and functionality of your company.
Let us now look at the skills required to become a Machine Learning engineer.
To become a successful machine learning engineer, you need to develop a specified set of technical as well as non-technical skills. Let us first look at technical skills.
- Deep knowledge of Programming Languages.
One of the most important skills you need to develop is an in-depth understanding of programming languages like R, Python, Java, C++, etc. Python is considered to be a lingua-franca of Machine Learning. Along with programming languages, you should be clear in concepts like data structures, memory management, and classes.
Since you are required to make machines learn and draw conclusions from the patterns, you are required to have a thorough understanding of statistical concepts like mean, Gaussian distributions, standard deviations along with probability theorems. A knowledge of Calculus, Matrices and Linear Algebra is also required.
- Applied Mathematics
You are required to have a firm grip over applied mathematical concepts such as gradient descent, quadratic programming, partial differentiation and integration, convex optimization, etc.
- Signal Processing Techniques
Machine learning also includes solving problems via Signal Processing Techniques, because feature extraction is to be done many times. So the clear understanding of Time-frequency analysis and advanced signal processing algorithms such as Curvelets, Bandlets, Shearlets, Wavelets are also must-have skills.
- Neural Network Architectures
Some specific set of algorithms, neural networks are a class of models that exist within machine learning and have transformed machine learning. Almost all the problems solved by machine learning include neural networks as their processing units. These are responsible for performing various tasks like image classification, speech recognition, translations, speech-to-text, etc.
- Language, audio and video processing
The main task in machine learning is processing language, audio, and video inputs to extract useful insights and respond accordingly. For this, you need to have a knowledge of Fourier transformation and applied math.
Now that we are done with technical skills, let us now move towards non-technical skills that are a must-have.
On top of the list of non-technical skills comes excellent communication skills. That is because you are required to work with teams. Next comes the Industry Knowledge. You are required to know well how your industry works, and what are the challenges it is facing, and other issues.
It is mandatory to iterate on ideas rapidly to find out which one is the best. Rapid Prototyping may help you achieve this. Next, you are required to stay updated with what’s going on, related to the development of tools and techniques. To keep updated, you can go through research papers, webinars, blogs, and be a member of online communities.
Now that you are up with the skills you need to develop to become a successful machine learning engineer, you must know that there are certification courses available regarding the same. If you add this certification to your resume, you will definitely be the preferred choice against similar candidates without certification.
It is strongly recommended that you take up an online course and also free machine learning test questions that may help you pass the exam. Practice makes a man perfect. If you take up those practice tests, it will surely rejuvenate your confidence and make you start your journey to a successful machine learning engineer.