8 Ways You Can Succeed In Machine Learning

Everyone wants to make a good career in their respective fields just like people can make career in Machine learning. Machine learning will open immense opportunities for you in the industry. You can have better future with Machine learning skills as this career in high in demand. You can get a high paying job as a Machine Learning Engineer, Data Scientist, NLP Scientist, Business Intelligence Developer, and many more. It expected by experts that Machine Learning & Artificial Intelligence will make a business around $4 Billion by the year 2022. According to the surveys one third part of the companies have already started spending on Machine Learning and rest companies or industries are planning to do so.

Why you should work in Machine Learning?

In an industry of machine learning you will get many opportunities with great knowledge as well. You will get job opportunities in cyber security, face recognition, and so on. If you are curious about automation, algorithms, and data then this a right path you can choose for your career. There are many options you can choose within this career. People with machine skills are in great demand and little in supply, which helps to explain why these jobs are so valuable. There have even been tales of bidding wars for Artificial Intelligence expertise as big companies compete for the best minds in the field.

Industries are using Machine Learning

Image source: https://www.burtchworks.com/2018/06/12/2018-machine-learning-flash-survey-results/

8 Ways you can succeed in Machine learning career path

1. Understand what machine learning is: - Stating the obvious statement but it is equally important. Understanding machine learning and having experience is just like understanding basic mathematics behind it, understanding the alternative technology and having hands-on experience along with the technology is the key.
2. You should be curious about machine learning: - Machine learning is the only thing that is going to evolve in future, so you should be curious and must love to learn new things in Machine Learning. “Machine learning is in demand and is evolving quite rapidly in the last few years with new frame work, new technologies, new techniques, new languages and many more things to learn. This making people eager to learn”, says Florian Douetteau (Co-founder and CEO of Dataiku).
3. Be a team player: - If you are working in a machine learning profession you are most likely to work in a team, and that team would be comprise of a people who have directly interaction with the business team. And if you want to be a successful machine learning practitioner you must be able to work with a team. 
4. Translate business problems into mathematical terms: - Machine learning is a field which is practically designed for logical minds. Machine Learning is a mixture of Mathematics, Technology, and Business Analysis. You must have openness towards the business problems and must be able to articulate business problems into the mathematical machine learning problems.
5. Must have a background in Data Analysis: - Data analysts are in the perfect position to choose their career path in Machine Learning as the next part of their profession because having a data analytics mind set is like a way to think about causes, consequences, and discipline where you look at the data, you dig into it, and you understand what works and what not.
6. Learn Python and how to use machine learning libraries: - Experts recommend that people who want to build their career in machine learning should learn python first and then dive into the machine learning libraries for better career growth.
7. Take online courses and practice more: - Your ultimate goal is to expand your machine learning skills as much as you can. You can start learning by mixing online courses and tutorials to get better knowledge in this particular field. By practicing more you can become a expertise in this field and can earn more in great industries with higher opportunities.
8. Gain knowledge of the industry where you want to work in: - Every industry or company has its unique goal and desires. If that the case the better you understand the need or desire of your industry the better you work for them. You don’t need to be expert in each and everything someone from your team might help you but gaining little knowledge from everything can make things easy for you and you can work hassle-free for your organization.

Career options in Machine Learning

1. Business Intelligence (BI) Developer: - A Business Intelligence (BI) Developer should be expert in SQL, Python, Power BI, Databases. The role of BI developer is to use data analytics and Machine learning techniques to work on large amount of data and to make it better for decision maker of the business. 
2. NLP Scientist or Natural Language Processing: - Natural Language Programming Scientist should be expert in any language which human being can speak. In other words NLP Scientist trains the machine to interact with human beings. For this NLP should learn machine learning so that they can train the machine to talk in different languages which human beings use.
3. Data Scientist: - The role of a data scientist is somehow similar to BI developer. The data scientists have to work on data so that the decision makers of several businesses can make their decisions with the helped of the data on which the data scientists have worked.
4. Machine learning engineer: - Machine learning engineer works on machine to make future predictions. Machine learning engineer must have knowledge of Python, Scala, Data Modeling, Programming, and Machine learning algorithms, statistics, system design and probability. These things will surely make you a Machine learning engineer.
5. Data Architect: - A data architect ensures that the data solutions are built for design analytics applications and performance for multiple platforms. Data Architect works with the system designers, users, and developers in a project team.
6. Enterprise Architect: - An enterprise architect would be responsible for aligning the organization’s strategy along with the technology. An enterprise architect must have complete understanding of businesses and its technology needs in order to design the system architect.
7. Big Data Engineer or Data Engineer:- A data engineer is responsible for creating and managing company’s big data infrastructure and tools, it is someone who know how to get results quickly from a vast company’s data.

Machine Learning skills that are required

Now you know that you can have several career options in machine learning and now you must read what are the skills that are needed in this career path? – 

• Signal Processing Techniques: - This skill is very important in Machine learning. You may have to work with several signal processing techniques including shearlets, bandlets, contourlets, and curvelets.
• Data evaluation and modeling: - An important part of this machine learning is Data evaluation and modeling. You can use various methods such as regression and classification to measure the error or accuracy of the given model. You must have an evaluation strategy to work on.
• Programming Languages: - To get a better job opportunity you should know different programming languages. Such as – Java, R, Python, and C++. These languages will surely help you to work on various levels of your projects in your organization. 
• Statistics and Probability: - Your understanding of algorithms has a lot to do with the knowledge different theories. Such as Hidden Markov Theory, Gaussian Mixture, and Naïve Bayes. Well if you are not good at statistics and probability you will find difficulty to understand these algorithms.
• Communication Skills: - The person should know how to translate completely technical terms to a non-technical team, so that they can better understand the project.
• ML Algorithms: - You must know how machine learning algorithms work and which will fit perfectly in the situation is very important. You have to develop an understanding of different subjects like Partial differential equations, Gradient Descent, Quadratic Programming, Convex Optimization and many more. 

Reasons why should you pursue your career in Machine Learning?

An industry needs Machine Learning and Artificial Intelligence experts so that they can work with them to get power as a leading industry in the market. Here are some few reasons which are listed below:-

1. The future of Machine Learning and artificial Intelligence: - Machine learning has the future for the industry and for your job prospects and this career is not going to die so soon not at least in a decade or two. All you need to do is gain proper knowledge in your respective field so that you can earn more with a job security.
2. Augmented career growth: - We must accept the fact that this career is in its early stage and people are yet to adopt this new career. But surely they will do because this is an expanding career for newbies out there.
3. Challenging work: - This career is mainly for those who are keen interested in real life projects and are ready to take any challenges. The person should know how to make a solution for every problem so that they can make solution for both individuals and businesses at same level.
4. Option to opt for Data Science: - People with machine learning skills have so many doors open to them with this career path. With the right set of skills people can also become a data scientist. As a data scientist you will get knowledge, challenges, and opportunities.

Conclusion

A job in machine learning allows you to keep up with the digital transformation that is sweeping practically every industry. Professionals with machine learning skills have various options available to them, from which they can select the one that most interests them and pays them according to their abilities. From smartphones to chatbots everything is going to depend on the machine learning and Artificial Intelligence, so it is the best time for you to start learning machine learning course to get a dream job in your dream company. If we particularly talk about machine learning engineers, there was an increase for job opportunities in the year of 2015-2018. The average salary in India for Machine Learning Engineers is Rs. 7 Lacs per annum. The article titled “Why should you choose your career in Machine Learning?” has mentioned all the aspects for you, so that it will make easier for you to decide your path in this profession.

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