R for Data Science and Machine Learning
R for Data Science and Machine Learning
R for Data Science and Machine Learning
R in data science is used to deal with, store and break down data. It can be used for data analysis and statistical demonstrating. R is an environment for statistical analysis. R has various statistical and graphical capabilities.
Table of Contents
- 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
- Shiny
R for Data Science and Machine Learning FAQs
Is it easy to learn R?
R is a great language for programming beginners to learn, and you needn't bother with any prior experience with code to get it. Nowadays, R is easier to learn than any time in recent memory thanks to the assortment of packages.
What is the role of R?
R is a Procedural Programming Language that breaks down a task into a sequence of Stages, Processes, and Subroutines. This allows R to easily transform data into significant Statistics, Graphs, and foster Statistical Learning Models for predictions and inferences.
Is R enough for data science?
Assuming you're passionate with regards to the statistical estimation and data visualisation portions of data analysis, R could be ideal for you. If, then again, you're interested in turning into a data scientist and working with large data, artificial insight, and profound learning algorithms, Python would be the better fit.