Every day the world is advancing into the new level of industrialization and this has resulted in the production of a vast amount of data. And, at initial stages, people started considering it as a bane, but later they found out that it’s a boon. So, they started using this data in a productive way. Big data and machine learning are terminologies based on the concept of analyzing and using the same data. Let’s get into more details.
According to Wikipedia, Big Data “is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.”
In simple words, it is used to find the patterns and predict the data based on that.
According to Wikipedia, Machine Learning “is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead.” It is seen as a subset of artificial intelligence.
Simply, it is the concept in which the machine uses the data to learn and perform actions.
How is Big Data different from Machine learning?
- Big Data can be implemented in various fields. This includes the banking sector, financial analysis, media & communication industry and many more whereas machine learning is mainly focused on the automation of things and thus this is mostly limited to technical fields.
- Big data mainly focus on collecting a large amount of data and predicting the patterns in the data, whereas Machine Learning is the concept of learning from the trained data and using it to predict the data.
- Big data is the concept of dealing with a large amount of data, whereas machine learning is the concept of dealing with the subsets of these trained datasets.
- Big data analytics basically uses the classification and sequence analysis to predict the patterns, whereas machine learning uses the same algorithm to learn from the collected data automatically.