R Ultimate 2024: R for Data Science and Machine Learning

R Ultimate 2024: R for Data Science and Machine Learning, available at $79.99, has an average rating of 4.83, with 204 lectures, based on 193 reviews, and has 2811 subscribers.

You will learn about learn all aspects of R from Basics, over Data Science, to Machine Learning and Deep Learning learn R basics (data types, structures, variables, and more) learn R programming (writing loops, functions, and more) data im- and export basic data manipulation (piping, filtering, aggregation of results, data reshaping, set operations, joining datasets) data visualisation (different packages are learned, e.g. ggplot, plotly, leaflet, dygraphs) advanced data manipulation (outlier detection, missing data handling, regular expressions) regression models (create and apply regression models) model evaluation (What is underfitting and overfitting? Why is data splitted into training and testing? What are resampling techniques?) regularization (What is regularization? How can you apply it?) classification models (understand different algorithms and learn how to apply logistic regression, decision trees, random forests, support vector machines) association rules (learn the apriori model) clustering (kmeans, hierarchical clustering, DBscan) dimensionality reduction (factor analysis, principal component analysis) Reinforcement Learning (upper confidence bound) Deep Learning (deep learning for multi-target regression, binary and multi-label classification) Deep Learning (learn image classification with convolutional neural networks) Deep Learning (learn about Semantic Segmentation) Deep Learning (Recurrent Neural Networks, LSTMs) More on Deep Learning, e.g. Autoencoders, pretrained models, … R/Shiny for web application development and deployment This course is ideal for individuals who are R beginners interested in learning R or data science practitioners who want to deepen their knowledge or developers who want to learn different aspects of Machine Learning It is particularly useful for R beginners interested in learning R or data science practitioners who want to deepen their knowledge or developers who want to learn different aspects of Machine Learning.

Enroll now: R Ultimate 2024: R for Data Science and Machine Learning

Summary

Title: R Ultimate 2024: R for Data Science and Machine Learning

Price: $79.99

Average Rating: 4.83

Number of Lectures: 204

Number of Published Lectures: 204

Number of Curriculum Items: 204

Number of Published Curriculum Objects: 204

Original Price: €69.99

Quality Status: approved

Status: Live

What You Will Learn

• learn all aspects of R from Basics, over Data Science, to Machine Learning and Deep Learning
• learn R basics (data types, structures, variables, and more)
• learn R programming (writing loops, functions, and more)
• data im- and export
• basic data manipulation (piping, filtering, aggregation of results, data reshaping, set operations, joining datasets)
• data visualisation (different packages are learned, e.g. ggplot, plotly, leaflet, dygraphs)
• advanced data manipulation (outlier detection, missing data handling, regular expressions)
• regression models (create and apply regression models)
• model evaluation (What is underfitting and overfitting? Why is data splitted into training and testing? What are resampling techniques?)
• regularization (What is regularization? How can you apply it?)
• classification models (understand different algorithms and learn how to apply logistic regression, decision trees, random forests, support vector machines)
• association rules (learn the apriori model)
• clustering (kmeans, hierarchical clustering, DBscan)
• dimensionality reduction (factor analysis, principal component analysis)
• Reinforcement Learning (upper confidence bound)
• Deep Learning (deep learning for multi-target regression, binary and multi-label classification)
• Deep Learning (learn image classification with convolutional neural networks)
• Deep Learning (learn about Semantic Segmentation)
• Deep Learning (Recurrent Neural Networks, LSTMs)
• More on Deep Learning, e.g. Autoencoders, pretrained models, …
• R/Shiny for web application development and deployment

Who Should Attend

• R beginners interested in learning R
• data science practitioners who want to deepen their knowledge
• developers who want to learn different aspects of Machine Learning

Target Audiences

• R beginners interested in learning R
• data science practitioners who want to deepen their knowledge
• developers who want to learn different aspects of Machine Learning