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Book Overview & Buying
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Table Of Contents
R Ultimate 2024 - R for Data Science and Machine Learning
By :
R Ultimate 2024 - R for Data Science and Machine Learning
By:
Overview of this book
Step into the world of R and elevate your data science expertise. This course begins with a hands-on introduction to R and RStudio, guiding you through data types, programming essentials, and file management. You'll master data import, manipulation, and visualization, exploring tools like ggplot2 and advanced libraries for dynamic and interactive graphics.
Advance into machine learning and deep learning concepts with practical applications. Covering regression, classification, clustering, and dimensionality reduction, you'll explore essential techniques for building predictive and analytical models. The course also delves into deep learning, including CNNs, RNNs, and autoencoders, ensuring you grasp modern AI methodologies.
The journey concludes with applied projects, featuring real-world datasets and challenges in shiny app development, dynamic reporting, and automation. By the end, you'll have the skills to build end-to-end data-driven solutions, positioning yourself as a competitive professional in data science and AI.
Table of Contents (29 chapters)
Course Introduction
Data Types and Structures
R Programming
Data Import and Export
Basic Data Manipulation
Data Visualization
Advanced Data Manipulation
Machine Learning: Introduction
Machine Learning: Regression
Machine Learning: Model Preparation and Evaluation
Machine Learning: Regularization
Machine Learning: Classification Basics
Machine Learning: Classification with Decision Trees
Machine Learning: Classification with Random Forests
Machine Learning: Classification with Logistic Regression
Machine Learning: Classification with Support Vector Machines
Machine Learning: Classification with Ensemble Models
Machine Learning: Association Rules
Machine Learning: Clustering
Machine Learning: Dimensionality Reduction
Machine Learning: Reinforcement Learning
Deep Learning: Introduction
Deep Learning: Regression
Deep Learning: Classification
Deep Learning: Convolutional Neural Networks
Deep Learning: Autoencoders
Deep Learning: Transfer Learning and Pretrained Networks
Deep Learning: Recurrent Neural Networks
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