Machine Learning e Data Mining in R
This program provides a pragmatic introduction to machine learning and data mining using R, encompassing fundamental techniques and tackling significant data analysis difficulties.
Description for Machine Learning e Data Mining in R
Features of the Course:
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Data Manipulation and Visualization With R: Acquire skills in importing, manipulating, and visualizing data utilizing R and the tidyverse packages, including dplyr and ggplot2.
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Supervised and Unsupervised Learning in R: Acquire the expertise to identify and address supervised and unsupervised learning challenges utilizing R packages such as leaps, glmnet, and pls.
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Comprehending Shallow and Deep Neural Networks: Understand the distinctions between shallow and deep artificial neural networks, crucial for addressing various machine learning challenges.
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Confronting Data Obstacles: Comprehend the resolution of persistent data challenges like as collinearity, overfitting, regularization, and knowledge transfer.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by University di Napoli Federico II
Duration: 3 weeks at 10 hours a week
Schedule: Flexible
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