in a single line:
Data Science is an area of expertise where you Analyze the Analytical data that you found after Mining the Big Data.
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What is ML (Machine Learning), AI (Artificial Intelligence), DL (Deep Learning), IoT (Internet of Things)?
ML is sometimes quoted as the core-link between Data Science (a stream where you find meaning out of data) and AI (a stream where you want to make machines self-intelligent). ML; from the mentioned perspective; lets AI use DS.
Machine learning is a set of algorithms that train on a data set to make predictions or take actions in order to optimize some systems. For instance, supervised classification algorithms are used to classify potential clients into good or bad prospects, for loan purposes, based on historical data. The techniques involved, for a given task (e.g. supervised clustering), are varied: naive Bayes, SVM, neural nets, ensembles, association rules, decision trees, logistic regression, or a combination of many.
When these Machine Learning algorithms are automated, as in automated piloting or driver-less cars, it is called Artificial Intelligence (AI).
If the data collected comes from sensors and if it is transmitted via the Internet, then it is machine learning or data science or deep learning applied to Internet of Things (IoT).
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What is Big Data?
Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.
This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data - i.e., we need not define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes). We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase. Also note that the definition can vary by sector, depending on what kinds of software tools are commonly available and what sizes of datasets are common in a particular industry. With those caveats, big data in many sectors today will range from a few dozen terabytes to multiple petabytes.
Data Science is an area of expertise where you Analyze the Analytical data that you found after Mining the Big Data.
What is ML (Machine Learning), AI (Artificial Intelligence), DL (Deep Learning), IoT (Internet of Things)?
ML is sometimes quoted as the core-link between Data Science (a stream where you find meaning out of data) and AI (a stream where you want to make machines self-intelligent). ML; from the mentioned perspective; lets AI use DS.
Machine learning is a set of algorithms that train on a data set to make predictions or take actions in order to optimize some systems. For instance, supervised classification algorithms are used to classify potential clients into good or bad prospects, for loan purposes, based on historical data. The techniques involved, for a given task (e.g. supervised clustering), are varied: naive Bayes, SVM, neural nets, ensembles, association rules, decision trees, logistic regression, or a combination of many.
When these Machine Learning algorithms are automated, as in automated piloting or driver-less cars, it is called Artificial Intelligence (AI).
If the data collected comes from sensors and if it is transmitted via the Internet, then it is machine learning or data science or deep learning applied to Internet of Things (IoT).
_______________________________
What is Big Data?
Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.
This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data - i.e., we need not define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes). We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase. Also note that the definition can vary by sector, depending on what kinds of software tools are commonly available and what sizes of datasets are common in a particular industry. With those caveats, big data in many sectors today will range from a few dozen terabytes to multiple petabytes.
Source:
Datasciencecentral.com/profiles/blogs/difference-between-machine-learning-data-science-ai-deep-learning
Some parts of this post have also been copied from a answer written on Quora which picked its stuff from a Mckinsey report
Some parts of this post have also been copied from a answer written on Quora which picked its stuff from a Mckinsey report
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