The modern technologies such as Data science ,Machine learning and Deep learning are quite confusing in terms of their difference and definition. As they all are interconnected with each other. Although each has a distinct purpose and functionality. Let’s find out the relation between these technologies. Data Science is a much broader term than machine learning. Applying Machine learning and Deep learning techniques are aspects of data science. Data Science is basically the study of : Collecting data Storing data Processing data Describing data Modelling data Now modelling of data is basically done by two types : Statistical modelling Algorithmic modelling In statistical modelling we basically use very simple models for robust statistical analysis & statistical guarantees. (it is most suited for low-dimensional data) But in case of more complex relationship we use alternative approach (i.e algorithmic modelling) and build complex mod
Dat a Science is the science of - Collecting data Storing data Processing data Describing data Modelling data A data scientist takes that raw data whether that be from daily users or surveyed statistics and uncovers hidden insight that can help enable companies to make smarter business decisions. COLLECTING DATA - Data collection is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcome. Where does data come from? Traditional data may come from the basic customer records, or historical stock price information. Now consistently growing number of companies and industries use and generate big data. Consider social media communities, for example, Facebook, Google and LinkedIn or financial trading data. Temperature measuring grids in various geographical locations ,as well as machine data from sensors in industrial equipment also account t