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Top 10 R Packages Data Scientists & Machine Learning Career Enthusiasts Should Know
Over the past few years both demand & popularity for R language has increased exponentially. In addition to Python, R is also considered to be the most extensively used programming language across Data Science & Machine Learning platforms.
Let us have a look at the top 10 R packages for Data Science and Machine Learning.
Lattice-
Improving the on-base R graphics is the primary objective of Lattice package in R. This achieves it by providing better defaults and the ability to easily display multivariate relationships. The creation of trellis graph which is the inspiration for the creation of a powerful and elegant high-level data visualization system is supported by this package.
DataExplorer-
The initial & the most crucial phase in the process of Data Analysis or predictive modeling is Exploratory Data Analysis (EDA . EDA is the process where data modelers first examine the data & then generate relevant hypotheses to go ahead with the next steps.
This DataExplorer package aims towards automating most of data handling and visualization thereby presenting data modelers with a lot of time for studying and extracting insights encrypted inside the data.
DataExplorer-
The initial & the most crucial phase in the process of Data Analysis or predictive modeling is Exploratory Data Analysis (EDA . EDA is the process where data modelers first examine the data & then generate relevant hypotheses to go ahead with the next steps.
This DataExplorer package aims towards automating most of data handling and visualization thereby presenting data modelers with a lot of time for studying and extracting insights encrypted inside the data.
DALEX-
DALEX has the presence of various explainers that play a crucial role in understanding the link between input variables and model output. The single_variable() explainer extracts conditional response of a model as a function of a single selected variable.
This R library has the presence of advanced tools sets which makes it possible to understand the way complex models work.
DPLYR-
DPLYR is considered as a powerful R-package whose function is to transform and summarize tabular data with rows and columns. In addition, DPLYR has also got the presence of another useful function which helps in performing the “split-apply-combine” concept.
ESQUISSE-
This R package helps the data modelers to explore & extract the valuable information encrypted inside the data at a very high speed.
This package will also lets them to draw bar graphs, curves, scatter plots, histograms, then export the graph or retrieves the code generating the graph.
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