Machine Learning (ML) is the study of getting computers to perform distinct automated activities using algorithms and software applications that can be utilized in predicting different outcomes. During a time of digitization in all the business organizations, machine learning tools are a great fit to accelerate the growth of IT industries with great force and capacity.
It is pervasive to an extent that probably everyone is using it gazillion times unknowingly for doing regular chores. Machine Learning is recognized in internet search engines for instance speech recognition, spam detection in emails, e-commerce websites for product recommendation and in banks to detect unusual transactions.
What is Machine Learning?
Machine Learning is similar to artificial intelligence that permits software applications to anticipate different business outcomes using historical data and bring out fresh output values.
Now, the question arises why it is important in our everyday lives and the answer is explicitly very precise and clear. Machine learning facilitates new trends analyzing customer behaviour which aids in the development of new products in various enterprises. For example, leading companies such as Uber, Facebook, Google make their decision-making strategies revolve around these algorithms which is why they have succeeded in expanding their domain to a wider space within a limited time period.
Who is a Machine Learning Engineer?
Machine learning engineer is a computer technician who has specialized in the art of researching, building, and designing running software to automate the process of predictive models. The job of an ML engineer is to leverage large amounts of data sets and to generate algorithms that are capable of making meaningful predictions.
Who can be a Machine Learning Engineer?
There is no pre-requisite to step into the career of machine learning. During a phase of fast-paced technology, the job market is suffused with high-end demand for people who have machine learning prowess to stimulate organizational decorum. However, if a person is a tech-enthusiast, it will be easy for him to grasp the basics of machine learning at a higher speed which will be added as an advantage to land in a machine learning career.
What are the career opportunities in Machine Learning?
Some of the machine learning career paths of 2022 are as follows:-
- Machine Learning Engineers – they develop platforms for administering machine learning projects.
- Natural Language Processing (NLP) Scientists – With the use of computers, they try to comprehend human language.
- Business Intelligence Developer – A BI developer examines the market trends.
What makes Data Scientists different from ML Engineers?
There is a lot of confusion that is going around the roles of ML engineers and data scientists because both are relatively brand new terms used in the job market. Before going any further, let’s address the distinction between machine learning and data science.
Machine learning is a branch of artificial intelligence that enables computers to perform business-oriented activities using software applications whereas data science is the process of studying and analyzing data to carve out meaningful decisions.
If you look at the two roles, data scientists are involved in the analytical works trying to decipher which machine learning algorithm to use and they build the model for testing.
On the flip side, machine learning engineers employ the model to ensure it is working in different applications using big data tools and programming frameworks.
What is the ML Engineer Salary in India?
As per Glassdoor records, the average salary of a machine learning engineer in India is INR 8,14,476/- in a year. In the Bangalore location, an ML engineer earns a minimum salary of INR.8,69,195/-
The countries with the highest payout for machine learning engineers in descending order are as follows:-
- The United States – USD $120k/-
- Australia- USD $111k/-
- Israel – USD $88k/-
- Canada – USD $81k/-
- Germany – USD $80k/-
- Netherlands – USD $75k/-
- Japan – USD $70k/-
- United Kingdom – USD $66k/-
- Italy – USD $60k/-
- France – USD $55k/-
Refer the article to know the Cost of Machine Learning Certification in 2022.
How to learn Machine Learning in 2022?
The machine learning program takes around five months to complete which includes the first two months of theoretical training and the next three months of capstone projects and internships. There are subcategories of ML programs for candidates to get specialized in various categories.
- Machine learning Expert Training
- Machine learning foundation Training
- Machine learning-Tensorflow
- Machine learning with Python training
- Machine learning with R training
Syllabus- Modules covered in ML engineering program are Advanced Machine Learning Concepts, Random Forest (ensemble), Python Programming, Support Vector Machine, Natural Language Processing, Naive Bayes Clarifier, Artificial Neural Network (ANN), Tensorflow Overview, and Deep Learning Introduction
Watch the video – What is Random State in Machine Learning?
Skills– A Machine learning engineer should possess extensive data science and statistical knowledge for data processing and software development. A few of the relevant skills which are mandatory to have for an ML professional are mentioned below:-
- The first and foremost skill which is essential for an ML engineer to have is practical or hands-on experience in working on data science projects. The reason being is machine learning is not an academic concept. It is not important to make in-depth research on the nitty-gritty theoretical aspects.
- An ML engineer should be well versed in the fundamentals of computer programming. As the significant role of an ML engineer is to make computers work like human beings, an encyclopedic knowledge of the principles of computers becomes pivotal
- ML engineers should be proficient in statistics from the basics of data science as it is an integral part of machine learning. They should also be thorough with the probability concepts like Markov models, Bayesian principles, etc.
- Proficiency in Data modelling is inevitable for an ML Engineer as data modelling techniques are used in machine learning to figure out data set classification.
Datamites is one of the prestigious institutes which provides global training for Machine learning programs inculcating projects and internships for hands-on experience. DataMites institute accredited from IABAC.
In addition to training, candidates will be thoroughly groomed for placement programs which mainly incorporate resume building, mock interviews, job-ready assessments, and virtual job fairs. Seemingly, these activities are more than sufficient for them to land high-profile jobs.
Check out the below video for Machine Learning Model Deployment.