Future of Machine Learning

Future of Machine Learning

Machine learning is being predominantly used everywhere. Literally speaking, Machine Learning is everywhere right from Alexa, Siri, Social Media, and Search Engines to Traffic Predictions, Video Surveillance, Malware Filtering, Online Customer Support, etc,.With the help of machine learning programming has been made simpler and accurate. Machine learning professionals are in high demand. In this article, we will learn about machine learning, career opportunities, etc.,


What is Machine Learning?


Machines Learning is the power of machines to perform tasks without being explicitly programmed. It uses stored data to learn and later use this learning to make human work easy.


According to Tom M. Mitchell, an American Computer Scientist, “A computer program is said to learn from experience E with respect to some class of task T and performance measure P if its performance at the task in T, as measured by P, improves with experience E.” In other words, machines are learning by themselves. Don’t freak out! Machine learning depends on programming, algorithms, and logic to collect data and find a pattern among these data. Afterward, machine learning uses data to make a prediction. The bigger the volume of data, the more accurate is the prediction. One example of data learning in which we all can relate to – If you stay engaged to a certain type of story in Facebook, then you will definitely cross related posts when you next time log in. This is because Facebook algorithms use your data history to predict the stories, videos or memes you like.


Limited not only to data prediction to enhance the user experience, but machine learning is also a field bigger than that. Machine Learning has its applications in the healthcare industry too. Certain disease like cancer is hard to predict in the initial stages. With the help of artificial intelligence and machine learning, it has become reasonably easy to predict initial stage cancer. IBM Watson is helping in this scenario. It is using integrating cognitive computing with genome-based tumor sequencing to make an early diagnosis.


There are other applications of machine learning in an arena like Neural Networks, Self Organizing Maps, Fraud Detection in Finance, Product Recommendation in Retail, Dynamic Pricing in Travelling and many more.


How to start a course in Machine Learning?


There are many online channels providing courses in Machine Learning. Some prerequisites are there before you start a course in machine learning. You need programming language knowledge either in C++, JAVA, R or Python. Mostly, industrial works are done on Python and R. If you have knowledge over C++ or JAVA, then you will learn Python in no time. Unlike C++ and JAVA, Python and R syntax are easy.


You also need to have good grip on probability and statistics, machine learning algorithms, data modeling and evolution, software engineering and system design.


At the time of learning, you will understand how easy it actually is – machine learning. Mainly, software engineering skills are the key to become a great Machine Learning Engineer.


Career Opportunities


Machine Learning can gift you jobs that you were dreaming of. Here are some fields where a Machine Learning Engineer works 


1. Software Engineering

2. Software Development

3. Machine Learning Engineer

4. Data Architecture

5. Research Scientist (AI)


Courtesy: Higher Education Review


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