Machine learning is one of the core concepts of data science and deals with the predictive analysis of data through the use of algorithms. It is closely related to computational statistics and also makes use of data-driven predictions that would help in developing a successful business model. For beginners who are willing to start a career in machine learning, there are a large number of skill sets which one needs to acquire over the course of time.
Here is a step-by-step approach to starting a career in machine learning. Read further to know more:
- Have strong programming and mathematical skills
Predictive analysis is an integral part of machine learning and to put this concept to use it is necessary that you have the right programming skills in languages such as Python and R. Along with this, you must be able to work of software development platforms such as SAS, Hive, Pig, Hadoop, etc. Mathematical concepts such as the ones related to probability, statistics, and linear algebra need to be studied in depth as they are crucial in data analysis and visualization.
- Learn about the theoretical concepts
Read more and more about machine learning so that you build a strong foundation over the time. Machine learning theory deals with a lot of algorithms related to data prediction, prepossessing, and business model interpretation. You must be thorough about all these concepts before you fully functionally step into the career.
- Get enrolled in machine learning courses
If you are new to machine learning, then it is always better that you take up some authentic machine learning course that would provide you with an original certificate. Some of the well-known universities offer such a course both online as well as offline. You can research about the same in order to hone your skills.
- Learn to work on different data sets
Problems are often based on the data sets which need to be solved with the use of machine learning algorithms for testing, regression, and clustering. You would then need to use different modeling approaches and figure out the solutions to the problems that might arise while working on them. You would also need to determine the performance metrics that suit a particular data science problem.
- Learn to write algorithms from scratch
Algorithms are an integral part of machine learning, and if you are looking forward to a career in the same, then you are specifically required to have the knowledge of algorithms and how you can use them to solve some of the major problems. Practice writing algorithms as much as you can as that would lay the foundation of working on complex problems in the future.
- Look at a problem with different perspectives
To come up with an efficient solution, you must be able to view a problem with different perspectives. This would help you in deriving and understanding the issues better and you can develop a better statistical model for a specific project.
- Use your machine learning knowledge on real-world projects
Once you are through with the machine learning courses and how you can use them for solving the real world problems, you should start applying your skills on the projects that would make an impact. Use the machine learning tools to build up complex yet effective business models.
As a machine learning professional, you are required to possess a wide range of skill sets which combine both analytical and technical knowledge in order to build up a successful business model. If you are interested in making a career in machine learning, then these above-mentioned skills and tips would surely take you a long way.