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Machine Learning Overview and Foundation Mathematics
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1
Fundamental principles of Machine Learning (ML)
To identify patterns in data, improve predictions over time, and make decisions based on data.
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2
Difference between unsupervised and supervised learning
Supervised learning uses labeled data for training, while unsupervised learning works with unlabeled data to find patterns.
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3
Linear Algebra in Machine Learning
Linear algebra is used for representation of data, transformation, and operations on vectors and matrices.
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4
Differential Calculus in Machine Learning
Differential calculus is used for optimization techniques such as gradient descent to minimize loss functions.
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5
R in Machine Learning
R is a programming language used for statistical computing and graphics, widely used in data analysis.
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6
caret package in R
The 'caret' package streamlines the modeling process by providing a consistent interface for various machine learning algorithms.
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7
ggplot2 package in R
The 'ggplot2' package is used for data visualization, allowing users to create complex graphics based on the grammar of graphics.
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