Machine Learning Assignment Help India
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What Is Machine Learning?
Machine Learning is the subset of Artificial Intelligence In which we performed all Classification, Regression, Clustering and more other AI related
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Supervised learning as the name specifies shows the presence of a superviser as an educator. Essentially supervised learning is a learning wherein we teach or train the machine utilizing information in which the target lables are present. Once the machine has been trained then we present it with data without the presence of a target variable. In the second case the machine itself determines the correct targets for the data presented to it. Some of the most famous Supervised
algorithms include: Support Vector Machines, Linear Regression, Logistic Regression, Naive Bayes, Linear Discriminanat Analysis, Neural Networks.
For more details about Supervised Learning read our blogs:
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Unsupervised learning as the name specifies has no superviser present, this means that there are no targets or labels present in the training phase. The data consists of just the feature variables and is grouped based only on the feature set. Some of the most famous Unsupervised algorithms in to-days time include: K-means clustering, K-NN, Principal Component Analysis, Singular Value Decomposition, Hierarchical Clustering.
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R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.
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Basic Syntax to Read Data:
meas <- read.csv("../Data/MEASLES_Cases_1909-2001_20150923120449.csv", na.strings = "NA", header = TRUE, stringsAsFactors = FALSE)
Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
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