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Data Science

This Category is all about Data Science. : – )

Programming with Python

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Motivation In order to do proper hands-on with a new language, it’s important to understand each part of it by applying live examples. Hence its syntax fully clear. Let’s start by playing with functions; Functions Simply create an add_numbers a function that takes two numbers and adds them together; add_numbers updated to take an optional…

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Hands-On with Supervised & Unsupervised Learning | Machine Learning

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Motivation In Machine Learning, all types including supervised, unsupervised and reinforcement learning have their own way of implementation. Let’s do hands-on with them; Supervised Learning It’s the “Task Driven” (Predict next value). Here, we teach the model! then with that knowledge, it can predict unknown or future instances. Let’s implement the simple code in the jupeter…

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AI vs ML vs DL

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JumpStart with Hadoop

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Motivation; Whenever we will hear about Big Data implementation and its tools, we would definitely hear about Hadoop community. According to IBM analytics, some companies are delaying data opportunities because of organizational constraints. Others are not sure what distribution to choose and still, others simply can’t find time to mature their Big Data delivery due to…

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Up & Running with Big Data

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Motivation Big data is an amount of data that you cannot deal with using traditional methods and it’s very relative because big data five years ago is not big data today so it’s constantly evolving. I think it’s when you have a great amount of data. Not only can you not store it, but you…

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JumpStart Programming with Python 3

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Motivation; Well, if you want to play with data and deal with complex analytics problems then Python is the best for you. We can use Python for developing complex scientific and numeric apps. Python is designed with features to facilitate data analysis and visualization. The syntax in Python helps the programmers to do coding in fewer steps as…

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Understanding of Data Science Methodology

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Motivation: It’s all about the different methods used in data science. Data Science Methodology: There is the following methodology used in data science which can further categories into different phases; From Problem to Approach Business Understanding Analytical Approach Working with Data Data Requirements Data Collection Data Understanding Data Preparation Deriving the Answer Modeling Evaluation Development Feedback…

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JumpStart Into Big Data With HDInsight

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What would happen when the volume of your data increased repeatedly over time and you need high velocity at the same time. Not only that but you have a different variety of data and Variability also exist in your data. So how would you handle all that data? If we particularly talk about an existing…

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