R Ultimate 2024 - R for Data Science and Machine Learning

Master R for Data Science, Visualization, and Machine Learning in 2024

Created by Bert Gollnick

Explore R programming from the ground up and learn how to apply it to data science and machine learning. You will move from the basics of R and RStudio to advanced analytics, visualization, and modern AI techniques. Build practical skills to analyze, model, and visualize data for real-world applications.

Packt | Sep 2023 | 1336 min

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LevelIntermediate

CategoriesData Science, Statistical Analysis and Predictive Modeling, R

1Course Introduction
2Data Types and Structures
3R Programming
4Data Import and Export
5Basic Data Manipulation
6Data Visualization
7Advanced Data Manipulation
8Machine Learning: Introduction
9Machine Learning: Regression
10Machine Learning: Model Preparation and Evaluation
11Machine Learning: Regularization
12Machine Learning: Classification Basics
13Machine Learning: Classification with Decision Trees
14Machine Learning: Classification with Random Forests
15Machine Learning: Classification with Logistic Regression
16Machine Learning: Classification with Support Vector Machines
17Machine Learning: Classification with Ensemble Models
18Machine Learning: Association Rules
19Machine Learning: Clustering
20Machine Learning: Dimensionality Reduction
21Machine Learning: Reinforcement Learning
22Deep Learning: Introduction
23Deep Learning: Regression
24Deep Learning: Classification
25Deep Learning: Convolutional Neural Networks
26Deep Learning: Autoencoders
27Deep Learning: Transfer Learning and Pretrained Networks
28Deep Learning: Recurrent Neural Networks
29Shiny

What You Will Learn

You will learn by doing, working through coding labs and real-world projects that reinforce each concept. Practical exercises and interactive examples help you understand both the theory and application of data science, machine learning, and deep learning in R. By applying new skills to hands-on challenges, you'll build confidence and expertise.

Key Features

Master data manipulation and visualization using R and popular libraries
Build and evaluate machine learning models for real-world data problems
Apply deep learning and automation techniques to create end-to-end solutions

Target Audience

Perfect for aspiring data scientists, analysts, and professionals looking to use R for data-driven work. If you are a beginner with some programming experience or an experienced analyst aiming to expand your skills, you'll find practical tools and knowledge to advance your career in data science and AI.

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