Topics covered:Introduction and implementation in pythonImplementation in RIntroduction of Random forestImplementation in python of Random forestImplementation in R of Random forestIntroduction of XGBoost and implementation in pythonImplementation in R of XGBoostTime series analysisAnalytical decision makingTheory of entropy and information gainOverfitting and underfittingStopping rules, cross-validation, and […]
Topics covered:<> About tableau, prerequisites and features, installation and connect to data.<> Data visualisation, Filters, Drill down and up, forecasting and trend lines<> Clustering, dashboard, story- bringing it all together, end notes, LOD, order of operations and blending and joining.
Topics covered: Subqueries, Advantage and disadvantage,Concept of key field,Define joins and types of joinsAliases and pre-qualifersModify strings (Concatenating, trimming, changing case and using the substring functionDate and time stringsUse case statementsData governance and profilingFundamental principles when using SQL in Data ScienceTips and tricks to apply […]
Understand the naïve Bayes classifier on an intuitive level, and learn that the naïve Bayes classifier is a probabilistic type of classifier because we first calculate the probabilities and based on probabilities we decide which class to put a new data point in. What you […]
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the […]
Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to efficiently work with Python. In recent years, a number of tools have been built specifically for […]
R in data science R is a very popular language in academia. Many researchers and scholars use R for experimenting with data science. Many popular books and learning resources on data science use R for statistical analysis as well. Since it is a language preferred […]
What is R? Introduction to R R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers […]
What is Python?Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for:web development (server-side),software development,mathematics,system scripting. What can Python do?Python can be used on a server to create web applications.Python can be used alongside […]
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