Healthcare, Food-tech, Banking & Financial Services, Retail, E-Commerce – Machine Learning is becoming a crucial component of all of these industries with every passing second. From refrigerators that tell you when you are out of food, to watching shows/movies based on the recommended section by Netflix, you are surrounded by Artificial Intelligence.
With the amount of data that is produced every day in the world, Machine Learning is the perfect tool to utilize it for solving real-world problems, and not just problems it is improving the quality of life. But wait, before we go on raving about how cool Machine Learning is, let us tell you what it exactly is.
What is Machine Learning?
The term Machine Learning was coined by IBM’s Arthur Samuel in the year 1952. As per Stanford University’s definition, it is – “the science of getting computers to act without being explicitly programmed.” To put it simply, Machine Learning is a branch or type of Artificial Intelligence which enables software applications to predict the future/outcome by using historical data, and with continuous iterations, the predictions keep getting better.
The advancement in the field of Machine Learning has opened up a new world. You wouldn’t even know but you are surrounded by its application in your day-to-day life. Not just individuals but businesses are maximizing their profits and optimizing their products/services through Machine Learning.
Wanna know how? We have listed below a few examples:
- Personalized recommendations on streaming platforms
- Image recognition used in identifying cancerous X-rays
- Predicting a fraudulent transaction
- Self-driving cars
- Speech recognition – converting speech into text
And the list can go on.
There are Four Types of Machine Learning Algorithms
- Supervised Learning
- Semi-Supervised
- Unsupervised Learning
- Reinforcement Learning
What Does a Machine Learning Expert Do?
Machine Learning engineers are software programmers & IT specialists who design Artificial Intelligence systems models that help the machine learn & make predictions with minimal human intervention.
- Creating & designing Machine Learning systems and models
- Identifying & using the datasets to enhance the predictive models
- Coordinating with cross-functional teams as part of optimizing the entire process
- Training the Machine Learning models by ingesting data
- Performing statistical analysis and conducting tests and experiments
- conducting machine learning tests and experiments
- Deploying Machine Learning models initially as a prototype and then later as API
- Use relevant software libraries and work with ML algorithms
- Understanding the business requirements and communicating with the stakeholders
- Ensuring the data is of the highest quality via data cleaning
A Bachelor’s Degree
An undergraduate degree in data science, mathematics, computer science, and computer programming is essential to build the basics of Machine Learning. As an aspiring Machine Learning expert, you must have an undergraduate degree in any of the earlier mentioned disciplines since it is a key requirement for most Machine Learning jobs.
Programming Languages
To become a Machine Learning expert, fundamentals of programming languages are a must, however, the level of expertise in the programming languages depends upon your use of Machine Learning. If you want to solve real-world problems via Machine Learning then proficiency in languages such as Python or R is a must.
A few programming languages that you can learn to get started with your Machine Learning career are:
- Python
- R
- Java
- C++
- Julia
Projects
Knowledge gained via learning & reading is great, but knowledge gained via practical application of the learned subject is going to set you apart. On your journey to becoming a Machine Learning expert, undertake a few data projects to build your portfolio and enhance your skills. A repository of projects on your resume can give you a head start in this world of cut-throat competition.
Reading, Courses, and Certifications
In order to stay at the top of your game, take up additional courses & certifications that will help you acquire more skills that you might have missed. While courses and certifications are great to amp up your knowledge, reading is something that is often overlooked. Read a variety of blogs on Machine Learning, see videos on YouTube, join communities on different platforms, and acquire knowledge from all the available sources to stay updated with the latest industry news & trends.
Resume
Having the right skills and educational qualifications should be enough to become a Machine Learning expert, but being able to communicate that information is equally important. The first contact you have with a possible employer is through your resume and if you don’t know how to create an effective resume, you might be missing out on a lot of golden opportunities.
Preparing for Interview
Once you have been shortlisted for the interview, prepare well in advance for a few common questions asked in a Machine Learning interview. Here are a few of those questions:
- What are the different types of Machine Learning Algorithms?
- How to differentiate between Machine Learning & Deep Learning?
- What is ‘naive’ in the Naive Bayes Classifier?
- What is a Decision Tree Classification?
- How to Handle Outlier Values?
- Why should we hire you?
Key Skills for a Machine Learning Expert
For you to become an expert in the field of Machine Learning, you should have the basic knowledge & skills of a data scientist and a software engineer, since the three professions are linked when it comes to Machine Learning
Here is a list of skills that you must acquire to become a Machine Learning Expert:
- Applied Mathematics
- Neural Network Architecture
- Data Modeling
- Programming
- ML Libraries & Algorithms
- Software Designing
- Natural Language Processing
Proficiency in the following programs & tools will be a great addition to your knowledge base since these technical skills are in demand:
- TensorFlow
- Spark and Hadoop
- R Programming
- Apache Kafka
- Weka
- MATLAB
- Google Cloud ML Engine
- Amazon Machine Learning
- PytorchJupyter Notebook
- IBM Watson
Now that we have broadly covered the required technical skills let’s move on to the soft skills. A Machine Learning expert has to coordinate with cross-functional teams, hence it becomes necessary for him/her to have certain soft skills:
- Problem Solving
- Great at Communication
- Time Management
- Team Work
- Coordination
- Domain Expertise
Salary of Machine Learning Experts
Machine Learning is a highly lucrative career option, it is one of the highest-paying jobs in the world. To give you a broad range, Machine Learning experts earn around $ 76K to over $150K. However, not every Machine Learning job will pay the same. There are multiple factors at play that affect the salary of a Machine Learning expert:
- Experience level
- Geographical Location
- Company size
- Skills
- Educational Background
- Industry Expertise
Salary of Machine Learning Experts based on Years of Experience
- Salary for Entry-Level Professionals is ~$94K
- Salary for Mid-Level Professionals is ~$137K
- Salary for Senior Professionals is ~$165K
Salary of Machine Learning Experts based on Location
A Career in Machine Learning
What factors do we consider when choosing a career? Growth, demand, stability? Machine Learning offers all three and much more. A career in Machine Learning is highly lucrative and the industry is booming. There is no slowing down in the field of Artificial Intelligence, it is here to stay.
The global machine learning market is expected to reach $20.83B in 2024, growing at a CAGR of 44.06% between 2017 and 2024. The stats speak for themselves, if you want to look beyond statistics, just pause and observe the machines & technology you are surrounded with, your Alexa, Siri, high-end coffee-making machines, the platforms you use to watch movies, everything is using Machine Learning one way or another.
With the right qualifications, skills, and experience as mentioned in the above sections, you will be equipped with all the essentials of becoming a Machine Learning Expert.
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