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7 ways to be successful in Machine Learning

7 ways to be successful in Machine Learning

Machine Language is growing at a real fast pace with smart algorithms being used right from mobile applications and email to marking campaigns. If you want to land yourself a job in an in-demand field then setting yourself up with the best skills to work with artificial intelligence can be the best move you can make. Here are a few things that you can begin with in order to work towards a career in Machine Learning:

  1. Understanding what really Machine Learning is: This may sound like a really obvious point but just knowing what machine learning is on the surface and really learning it well, hands-on with in-depth understanding of basic analytics behind can be very different. So make sure you understand it properly.
  2. Being curious: Artificial Intelligence and Machine Learning are modern things which can only continue to evolve even more in the future so one must have a healthy sense of love and curiosity to learn new technologies and what goes into them. Machine Learning has been evolving at a rapid pace in the last few years with new languages, new techniques, new frameworks, new technology and new things to learn that makes it important for people to eagerly learn what’s new. This means one must be a pro about learning at all times; learning to upskill from time to time in the same technology (because upgrades happen very often). The first trait to being successful is being curious.
  3. Translation of business problems into mathematical terms: Machine learning is especially designed for the logically minded. As a career, it has the ability to roll math, business analysis and technology into one job. One must not only be able to focus on technology, and have intellectual curiosity but must also have openness towards problem solving in the business sphere. One should also be able to articulately turn a business problem into a mathematical machine learning problem and bring value at the end.
  4. Become a team player: The term, ‘machine learning; might get you to think of a single professional surrounded by machines and computers. This may have been true a few years ago when the field was still new to the IT industry, but today the dynamics have changed to a more collaborative one. Today, working in machine learning is usually working in a team that includes people who directly interact with the business. So one must be successful as a practitioner of machine learning, must also be a team player and interact with a business.
  5. Background in data analysis: Data analysts are professionals who can easily transition into a machine learning job role as the next step. In a role that is as important as this, an analytical mindset is a way to think about discipline, causes and consequences where one can look at data and know where to dig in, understand what can work best, what cannot etc.
  6. Learn Python and the use of Machine Learning libraries: Python is the most recommended programming language for machine learning by industry experts. Tensor Flow and Scikit-learn are popularly used.
  7. Attend a Data science bootcamp or a Blended Learning course: The goal is to broaden machine learning sillset as much as you can. It is recommended to start learning from online courses, especially the blended learning ones where you can get hands-on experience in online labs in the actual technology.

IIHT’s Blended learning course in Machine Learning can be taken as an all integrated one or can even be a module based one – you learn as you want in a live-interactive environment. The Blended Learning course encourages students in all the above points from the beginning, in some cases even through the award winning expert learning management system. For more details go to: aimlstack.iiht.com.

 

 

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