Batch norm and Layer norm are common normalization techniques. This brief video talks about the need for normalization and the types of norms in deep neural networks.
Normalization in Deep Neural Networks
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Category: Data Analysis
What is Median Absolute Deviation
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Understanding Mixed Data
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This brief video talks about mixed data and challenges dealing with mixed data when working with machine learning algorithms.
What is the difference between a BarChart and a Histogram ?
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A Histogram represents the distribution of a numerical variable. A bar-chart is typically used to compare numeric values corresponding to categorical variables. To construct a histogram: X-axis: Usually the range of values is binned. In other words, the entire range is divided into a series of intervals and each interval occupies a slot on the…
What is the difference between a Histogram and a Pareto plot ?
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A histogram is a bar graph that uses the height of the bar to convey the frequency of an event occurring. Each bar in a histogram corresponds to the frequency of occurrence of a specific event. A Pareto chart displays bars by the height of the bars, signifying the order of impact. It follows the Pareto philosophy (the 80/20 rule) through…
What is ACID property in a database? For data analytics tasks, do you need to care about ACID properties ?
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ACID properties are important in an RDBMS setting where operations are transnational and there are database updates involved as a part of the task. For instance a banking or an e-commerce application where real-time user data is updated typically needs an RDBMS. A data analyst typically handles structured data using query languages such as SQL. However,…
What are the different types of Joins while wrangling data?
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Here are the different types of the JOINs in SQL: (INNER) JOIN: Returns records that have matching values in both tables LEFT (OUTER) JOIN: Returns ALL records from the left table, and the matched records from the right table RIGHT (OUTER) JOIN: Returns ALL records from the right table, and the matched records from the…
Name a few problems that data analysts typically encounter?
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Some of the problems encountered by a data analyst are : Biased Data : Data could be biased due to the source from which it is collected. For instance, suppose you collect data to determine the winner of an electoral campaign, collecting from a specific region alone introduces one form of a bias, while collecting…
How do you handle missing data in an ML algorithm ?
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Missing data is caused either due to issues in data collection or sometimes, the data model could allow for missing data (for instance, the field ‘maximum credit limit on any of your cards’ might not make sense for someone who has no credit cards…). With missing data, typically the ML algorithm implementation might fail with…