What is Machine Learning
Machine Learning has been there all the time. Do you remember simple pattern recognition algorithms? These algorithms were the basis of machine learning. In today’s world, you can easily find more complex data analysis algorithms that can produce more reliable and precise results. Once programmed, these complex algorithms do not require any further programming. They can adapt and teach themselves based on the data provided to them. Consider a self-driving car, the machine learning algorithms implemented under the hood ensures that the car can learn and make decisions on its own. So more the car has been driven, more precise and accurate decisions it will take. Also, another major area of their use is the data security and malware detection. The modern antivirus solutions tend to learn from the usage of different users and create more sustainable software that can close major security loopholes. Fraudulent transactions can be detected and pointed out all with the help of these algorithms and some real-world data. Check out this interesting read from Forbes that discusses the major fields of use of Machine Leaning algorithms.
How to learn ‘Machine Learning’?
As per computer and technology experts, Machine Learning is going to be the most desired upcoming field. Also, the data engineers are paid a lot better than the conventional software developers/engineers. If anyhow the big-data interests you and you’ve been the stats king of your class. Or maybe just this field of engineering seems intuitive to you, you can make a career out of it. To get started, you need to be familiar with very basic computer science. Basic computer science is taught in the first year of most of the colleges around the world. But if you happen to be changing fields to computer science or if you just not study computers in college, you need to check out some basic computer programming. I would suggest Harvard’s CS50 anytime. It is available for free as an online course on EDx, and you can opt for a paid certificate as well. Once you’ve got the basics, you need to advance in statics, calculus and some other fields of mathematics. Now it will be time to learn real machine learning algorithms. I would suggest reading this article from Darshan Hedge. He was a Machine Learning Engineer at NVIDIA and currently working with Otto. In this article, he has discussed step by step process to become a successful Machine Learning Engineer.
Machine Learning and Artificial Intelligence
Machine Learning is usually confused with Artificial Intelligence but I say that Machine Learning is a subset of Artificial Intelligence. Artificial Intelligence is a wider concept of making computers and machine carry out tasks themselves. And Machine Learning is about adapting algorithms to the data provided. I would like to quote an answer at Quora from Xavier Amatriain: For example, you’d be surprised to hear that some of the self-driving cars that currently describing themselves as using AI, use very little machine learning and are mostly using rule-based systems. That said, I would agree that most AI applications nowadays are indeed using or will use ML soon. Read the complete answer here.
Microsoft Azure Machine Learning
Azure is a cloud service offered by Microsoft that lets you build and deploy m]powerful machine learning applications on the go. It is all about creating applications that use predictive analysis to report futuristic situations. Based upon the data, the applications can predict the upcoming errors and difficult situations. The complex algorithms used here belong to Xbox, Cortana and other Microsoft products as well. You can signup for a Microsoft Azure Machine Learning Studio for free or opt a 9.99$/month package that includes a lot of features. Machine Learning is a very interesting field to lay hands upon. If you happen to love data, you will definitely love Machine Learning. Check out all the articles that I’ve linked at various places in this post. They will for sure impress you and motivate you to read more about this interesting science.
