Machine Learning and Big Data: Why They Have to Work Together?

Analytics/ Analysis


machine learning and big data why they have to work together

Machine Learning is an Artificial Intelligence technology that allows computers to learn without having been explicitly programmed for that purpose. To learn and grow, however, computers need data to analyze and to train on. In fact, Big Data is the essence of Machine Learning, and Machine Learning is the technology that makes full use of the potential of Big Data.

What is Machine Learning?

If Machine Learning is not new, its precise definition remains confusing for many people.

Concretely, it is a modern science for discovering patterns and making predictions from data based on statistics, data mining, pattern recognition and predictive analysis. The first algorithms were created in the late 1950s. The best known of them is none other than Perceptron.

Machine Learning is very effective in situations where insights must be discovered from large and diverse datasets, i.e., Big Data. For the analysis of such data, Machine Learning is much more efficient than traditional methods in terms of accuracy and speed. For example, based on information associated with a transaction such as amount and location, and historical and social data, Machine Learning can detect potential fraud in a millisecond. Thus, this method is much more efficient than traditional methods for analyzing transactional data, data from social networks or CRM platforms.

Why Use Machine Learning with Big Data?

Traditional analytical tools are not powerful enough to fully exploit the value of Big Data. The volume of data is too large for comprehensive analysis, and the correlations and relationships between these data are too important for analysts to test all the assumptions to derive a value from these data.

Basic analytics are used by Business Intelligence and reporting tools to report sums, to do accounts, and to perform SQL queries. Online analytical treatments are a systematic extension of these basic analytical tools that require the intervention of a human to specify what needs to be calculated.

How it works?

Machine Learning is ideal for exploiting the hidden opportunities of Big Data. This technology makes it possible to extract value from massive and varied data sources without having to rely on a human. It is data-driven, and fits the complexity of the huge data sources of Big Data. Unlike traditional analytical tools, it can also be applied to growing datasets. The more data injected into a Machine Learning system, the more the system can learn and apply the results to higher quality insights. Machine Learning thus makes it possible to discover patterns buried in data more effectively than human intelligence.

Machine Learning courses are available on the web. In particular, they make it possible to start Machine Learning from Python. It is a computer language that is not quite hard to learn, and it allows neophytes to test applications using Machine Learning with Python. Likewise, Machine Learning’s open classroom allows you to discover the operation of this data processing technique for free.

Why Machine Learning Is Nothing without Big Data?

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