Why Machine Learning is a Crucial Skill for Budding Data Scientists?

Machine Learning

Arguably, we are living in a world where humans and machines coexist in harmony. For millions of years, we have been evolving and learning from our past experiences. In the same way, machines, too, are continually improving through new-age computing technology and machine learning algorithms fuelled by massive amounts of usage data generated.

The future of machine is massive and possibly, beyond the scope of our imagination. We leave this enormous responsibility on the shoulders of individuals, namely Data Scientists. Let us take a look at how machine learning is a desirable skill for upcoming data scientists and how getting a Post Graduate in Data Science can help you give wings to your dreams of pursuing a thriving career in data science.

The Machine Learning Landscape

Machine Learning (or ML) is a functionality born from pattern recognition and the theory that computers can learn to perform specific tasks, without being programmed to do so. As part of their investigation, researchers in the field of Artificial Intelligence (or AI) exposed computers to new data and leverage the iterative aspect of machine learning to see if the computers were able to adapt and learn from previous computations independently.

Subsequently, the machines were able to produce repeatable, reliable decisions, and results. In recent years, various machine learning algorithms have been developed to improve the computational ability of computers so that they can apply complex mathematical calculations and data representation techniques to big data and derive actionable insights.

Unlike statistical models, machine learning algorithms not only probe large volumes of data for structure (even if there is no definitive theory of what that structure is) but also validate any errors on new data through automated learning.

Why Machine Learning?

Data scientists need machine learning for the simple reason that it can help derive high-value actionable predictions and smart actions in real-time, without any human intervention.

As technology, machine learning helps analyse large chunks of data (both structured and unstructured) and eases the burden on data scientists. Overall, machine learning has significantly changed the way data extraction and interpretation are made replacing traditional statistical techniques with automatic sets of generic methods. Data scientists can quickly create precise machine learning models that can analyse more complex data in real-time and deliver faster, more accurate results identifying profitable opportunities and avoiding risks. 

The Impact of Machine Learning on the Data Analysis Avenue

For years, data analysis was all about trial and error an approach that becomes impossible to use in cases when there were large volumes of unstructured data sets. More heterogeneous the data sets, the more difficult it becomes to bring in new predictive models that are accurate. Traditional statistical solutions typically focused on static analysis (or analysis of data that was frozen in time) leading to inaccurate and unreliable conclusions.

Alternatively, Machine Learning proposes smart alternatives to analysing enormous volumes of data and producing accurate results such as efficient and fast data-driven models and algorithms for real-time data processing.

Machine Learning A Desirable Skill for Data Scientists

Data science and machine learning work hand in hand. The increasing usage of machine learning across industries acts as a catalyst pushing data science to increase its relevance. In other words, machine learning is only as good as the data it receives and the algorithm that is in place to consume the data. Going forward, organizations will need to leverage machine learning to improve their business strategies giving way to a more skilled workforce of data scientists.

This being said, data scientists need to develop their ability to evaluate machine learning and increase their employability. PG Courses in Data Science from reputable institutions such as Jigsaw Academy help both budding and experienced data scientists to acquire technical analytics skills in deep learning, Artificial intelligence, and machine learning.

Moreover, having a PG in Data Science enables you to solve non-standard problems through intuitive machine learning algorithms and statistical software tools. It is when you equip yourself with the right skills that you can go for the career of your dreams. And pursuing a PG in data science helps you develop the desirable skillset!