Descriptions
Machine Learning Scientist with R, master the essential skills to get a job as a machine learning scientist! You will expand your R programming skills with the toolbox to perform supervised and unsupervised learning. You will learn how to process data for modeling, train your models, visualize your models and evaluate their performance, and optimize their parameters for better performance. Along the way, you will get an introduction to Bayesian statistics, natural language processing, and Spark.
What you will learn
- Special feature Engineering in R
- Unattended Learning in R
- machine Learning in the Tidyverse
- intermediate Regression in R
- Cluster Analysis in R
- machine Careful learning in R
- Model with Tidymodels in R
- machine Learning with tree-based models in R
- dimensionality Reduction of R
- Support Vector machines in R
- Basics Bayesian data analysis in R
- Bayesian Regression modelling with rstanarm
- introduction to Spark with sparklyr in R
Machine Learning Scientist Specification with R
- Publisher : Data Camp
- Teacher: Brett Lantz
- Language: English
- Level: All levels
- Number of courses: 16
- Duration: 65 hours to complete the course
Contents of the Machine Learning Scientist with R
Pictures
Sample clip
installation Guide
Extract the files and watch them with your favorite player
Subtitles: English
Quality: 720p
Download links
Supervised learning in R classification
Supervised learning in R regression
Feature Engineering in R
Unsupervised learning in R
Machine Learning in the Tidyverse
Mean regression in R
Cluster analysis in R
Machine Learning with Caret in R
Modelling with Tidymodels in R
Machine learning with tree-based models in R
Dimension reduction in R
Support vector machines in R
Basics of Bayesian data analysis in R
Hyperparameter tuning in R
Bayesian regression modelling with rstanarm
Introduction to Spark with sparklyr in R
Password file(s): free download software
File size
1.57GB