Thanks to technologies like Machine Learning (ML) that today computer systems can learn from data, take important decisions and perform complex tasks, all with minimal human intervention.
But what is its relation with data science? Or is it important for an individual to master ML in order to seek a career in Data science?
This article will try to answer such questions-
Data Science
The field of data science is huge and encompasses a lot of activities related to utilizing data as a resource and helping organizations to benefit from untapping the value of data. Data scientists utilize their skills to solve complex problems when it comes to digging out important information out of huge chunks of unstructured data. Today a lot of organizations employ data scientists to make meaning of data and as data is the new ‘oil’, data scientists too are highly rewarded and revered across industries.
How is ML important in Data science?
Already quintillion bytes of data are being generated every day and no data set can be regarded as useless. Moreover, with the advent of Internet of Things much more data is expected to be generated and thus the task of Data scientists is only going to be tougher. Thus, they will be in search of sophisticated technologies capable of assisting them with the task of data analytics and utilization. And this is exactly where Machine Learning comes in!
Machine Learning is based on algorithms which are capable of developing themselves when exposed to new data and requires little or no human supervision at all. ML has found application in a number of industries and has yielded exceptional results. Most importantly however, ML has been great in building predictive models. Every language is working on ML without this you can not run any programme in the computer this ML language convert the other language to machine language so that’s why machine language is so important for every language and it sure your data which you are using in the coding .
Thus, ML can assist data scientists with automatic analysis of data and predictive or diagnostic analytics. Hence, ML has emerged as a vital technological skill for data scientists and if you are an aspiring data scientist you should definitely consider getting trained in ML!
How to acquire ML skills?
In order to acquire ML skills, you should opt for a good training course. A good training course will take care of imparting you with all the necessary skills to master ML and gain proficiency in applying ML for data science tasks. A good training course will also make sure that you learn the most popular and in-demand ML skills.
For instance, Python is the most popular programming language for ML and Python libraries like Pandas and Keras are highly preferred by professionals all over the world. Thus, a good Machine L anguage training course will see to it that you master python for ML. Python is very high level language like java you can work on any platform and it is secure and safe and it is easy to use and reliable with any platform. You can made any software with this language and in very big company mostly people use python language because this is safe compare to other language. The mostly big software are made on this language,
The best place to learn machine learning in India is Bangalore right now. Bangalore is the IT capital of India and is also the centre of data science and analytics industry of the country. Hence, you should opt for a training course in Bangalore to acquire skills from the best place to learn machine learning in India!
