Why you should know machine learning

Nowadays, all techies and industries are taking about a hot topic called machine learning. Many of software engineers with good programming skills are changing their career to machine learning. Also, when you sign in your social media account, you are getting notifications from various online training institutes about their course on machine learning, deep learning etc. You may wonder and think that why it’s happening? Why should we know machine learning? Why people are giving hype to machine learning? All of your doubts will clear at the end of this blog. 

In this decade the world has filled with various kinds of data such as pictures, music, word, spreadsheets, video .The machine learning will derive the meaning from all of these data by the help of a generic algorithm. It is a tool and technology that an expert can utilize to answer the questions with that data. It is the process of providing data to the particular machine so that it can predict new kinds of data when it comes in. Machine learning is a sub division of artificial intelligence. 

 One can explain it with thousands of real life applications of machine learning which you are doing on a daily basis either knowingly or unknowingly. For example,  if you provide lots of images of elephants to the machine and then give a new image of any other animal and the machine can tell whether that is an elephant or not. Moreover, all people are getting a plethora of emails on a daily basis.  Few of these emails are delivered in the inbox and few of them are into spam boxes. You may think that how can a computer differentiate all the above things. Here comes the role of machine learning. The program as well as the algorithm is developed in such a way that Gmail can predict which email is spam and which has to deliver in inbox. 

 ML has created huge changes in different types of industries like automation industries, finance and banking industry government organization, healthcare industry, retail and marketing, supply chain and logistics etc. Finance industry are using ML to prevent fraud and finding the patterns inside the data as well as government organization are availing ML to manage public safety and utilities 

Machine Learning Career opportunities: 

Machine learning techniques will make a machine to learn by it and producing perceptions from the data that can are able to increase the production level of an organization. Now, it has become more and more easy to collect a lot of data and because of this industries are looking at machine learning as the next level to develop their business. Therefore, there is a huge demand for machine learning experts. Unfortunately, there aren’t enough people to fill these roles because what is an industry need is a skillful person who can resolve a problem end to end as well as consider the business requirement and arise with a formulation of the right model and execute it. An individual who wants to start his career in machine learning should know how to process a data by using mathematical or statistical model and implement them through his programming skills. Companies are hiring people who are having these abilities. Recently people can find machine learning career prospects across different industries. Let’s look at the various job roles that are out there in the scope of machine learning 

1. Machine Learning Scientist/ Data scientists:-Machine learning scientist must an expert who can understand various kinds of machine learning models and underlying statistics. They could have the proficiency in probabilistic programming, statistics and fundamentals like linear algebra, optimization and so on. Furthermore, they are expertise to handle various toolkits available like scikit-learn, keras, tensor flow etc. They must efficient to take up a project and formulate the right model for the particular problem at hand and able to accomplish it. The insights given by the data scientist hold immense significance for decision makers of business.
2. Machine Learning Engineer:-  Machine  learning engineer are core software engineers. Responsibilities of Ml engineer are translating the insights to the theoretical models given by data scientist using machine learning algorithms.  ML engineers are fabricating production level model that are adept to handle terabytes of real time data to multiply the business value. To become an aspiring machine learning engineer you would need mastery in programming language such as python, JAVA, R, C++ and scala and basic mathematical knowledge. The demand and the salary make it one of the highest paying machine jobs. 
3. Data Analyst:- Data analyst is someone who works on the problems of decision support by looking at data and making inferences. They must be good at data visualization and data storytelling. To gather the insights from data, data analyst are using different type of database tools which varies from SQL to excel, tableau .They require cognizance in programming language such as python, R and JAVA etc. 
4. Research engineers:- The primary duty of research engineer is to develop the new technology products. These skilled people will improve the quality of existing system and processes by implementing research and creating knowledge from engineering. They conduct research in laboratories and come up with innovative and high impact data science projects. They will ensure the team has the necessary resources to undertake the assigned tasks to perform effectively and coordinating with stoke holders. The educational qualification of research engineer includes an advanced degree of masters or above. If you want to develop a career path in this area one should gain significant industry and professional knowledge and experience. 
5. Data engineers:-  The major responsibility of data engineer is to handles the data by figuring out the input and output of ML algorithm models. They are the responsible persons to collect all these various data from different sources and they should convert the data to a suitable format by cleaning and processing it. 

 How to Build a Machine Learning Career Path:  

Machine learning is one of the hardest skills to acquire this year. The total number of machine learning jobs has grown 600% over past two years. The field is exploding with opportunities and there are new discoveries made every single day. If you want to set foot in the world of machine learning career, you need to obtain some basic requirements that will help to improve your career, which has mentioned below. 

• The first step is to enhance your math skill because it plays a very important role in helping you to understand how machine learning and its    algorithm work. Among many mathematical concepts, probability and statistics, linear algebra, calculus is most important theories. 

• Developing a good programming skill is the next and major step to becoming a successful ML engineer. Most dominated programming languages are python and R followed by JAVA, JAVASCRIPT and C. 
• The third step is to gain some data engineering skills, which help you to analyze and process your data as soon as you get it. The data engineering skill must include the database management software or DBMS. Moreover, the person needs to be equipped with MySQL, ORACLE etc. 
• The forth step is to give focus on machine learning algorithms such as linear regression, logistic regression, decision tree, K- means, gradient boosting algorithm and so on. Learn all these algorithms in python, R since both these programming languages are part and parcel of ML. 
• The last step is to pick up the machine learning frame-work that can provide support to make the live of developers and users easier. The main Ml tools are scikit-learn keras, caffe, tensor flow etc. 

Of late, many of the training institutes are offering best and precise courses and training on machine learning techniques. If you are Novice in Ml with a qualified educational background or a software engineer with 1 or 2 year experience with less machine learning knowledge can grow or embark their career in ML by taking proper training. The career in machine learning is not only giving high salary package but it has career growth, job security and reputation and these qualities are making this career more popular among all IT field.