![R Ultimate 2023 - R for Data Science and Machine Learning [Video]](https://content.packt.com/V21665/cover_image_small.jpg)
R Ultimate 2023 - R for Data Science and Machine Learning [Video]
Subscription
FREE
Video + Subscription
$29.99
Video
$79.99
What do you get with a Packt Subscription?
What do you get with a Packt Subscription?
What do you get with Video + Subscription?
What do you get with a Packt Subscription?
What do you get with eBook?
What do I get with Print?
What do I get with Print?
What do you get with video?
What do you get with Audiobook?
Subscription
FREE
Video + Subscription
$29.99
Video
$79.99
What do you get with a Packt Subscription?
What do you get with a Packt Subscription?
What do you get with Video + Subscription?
What do you get with a Packt Subscription?
What do you get with eBook?
What do I get with Print?
What do I get with Print?
What do you get with video?
What do you get with Audiobook?
-
Free ChapterCourse 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
- Regression Types 101
- Univariate Regression 101
- Univariate Regression Interactive
- Univariate Regression Lab
- Univariate Regression Exercise
- Univariate Regression Solution
- Polynomial Regression 101
- Polynomial Regression Lab
- Multivariate Regression 101
- Multivariate Regression Lab
- Multivariate Regression Exercise
- Multivariate Regression Solution
-
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
- Convolutional Neural Networks 101
- Convolutional Neural Networks Interactive
- Convolutional Neural Networks Lab (Introduction)
- Convolutional Neural Networks Lab (1/1)
- Convolutional Neural Networks Exercise
- Semantic Segmentation 101
- Semantic Segmentation Lab (Introduction)
- Semantic Segmentation Lab (1/1)
-
Deep Learning: Autoencoders
-
Deep Learning: Transfer Learning and Pretrained Networks
-
Deep Learning: Recurrent Neural Networks
-
Shiny
About this video
R is a programming language and environment designed for statistical computing, data analysis, and graphical representation. R is widely used by statisticians, data scientists, researchers, and analysts for various tasks related to data manipulation, statistical modeling, and visualization. R is particularly well-suited for tasks involving data analysis, visualization, and statistics, chosen for its flexibility and a wide array of available tools.
This course takes us on a transformative journey through R programming, from foundational concepts to cutting-edge techniques. We delve into R’s fundamentals, data types, variables, and structures. We will explore R programming with custom functions, control structures, and data manipulation. We will analyze data visualization with leading packages, statistical analysis, hypothesis testing, and regression modeling. With regular expressions, we will understand advanced data manipulation, outlier handling, missing data strategies, and text manipulation. We will learn about ML with regression, classification, and clustering algorithms. We will explore DL, neural networks, image classification, and semantic segmentation.
Upon completion, we will create dynamic web apps with Shiny and emerge as skilled R practitioners, ready to tackle challenges and contribute to data-driven decision-making.
- Publication date:
- September 2023
- Publisher
- Packt
- Duration
- 22 hours 16 minutes
- ISBN
- 9781835082539