Data science deals with large amount of data and data scientist analyse that data to extract useful information from that data. This data analysis process involve 5 steps (1). In this post we will discuss those 5 steps involved in data analysis process and further we will explore some of the challenges we face during each step. In previous post we concluded that data science is the mixture of computing methods and statistical methods. In both data science and statistics, the core objective is to analyse the data. But in data science we automate some of the steps involved in...
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Category: Artificial Intelligence
Machine Learning is basically, to train machines (computers) by feeding them with huge amount of data. As a result they can predict/extract useful information based on previously available data. For example in order for a computer to recognize hand writing, we need to train that computer by feeding it with large amount of different handwriting samples.
forwardIntroduction to Data Science (Notes)
Data science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. Data Science is a super-set of the fields of statistics and machine learning (1). DSI (Data Science Initiative, 2015) website, gives us an idea about what Data Science is : "This coupling of scientific discovery and practice involves the collection, management, processing, analysis, visualization, and interpretation of vast amounts of heterogeneous data associated with a diverse array of scientific, translational, and interdisciplinary applications." Data Science vs Statistics: According to Data Science Association’s...
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