Machine Learning Scientist with R
4.5 /5- Offered byDataCamp
Machine Learning Scientist with R at DataCamp Overview
Machine Learning Scientist with R
at DataCamp
Master the essential skills to land a job as a machine learning scientist
Duration | 57 hours |
Mode of learning | Online |
Schedule type | Self paced |
Credential | Certificate |
Machine Learning Scientist with R at DataCamp Course details
Machine Learning Scientist with R
at DataCamp
Skills you will learn
What are the course deliverables?
- Supervised Learning in R: Classification
- Supervised Learning in R: Regression
- Unsupervised Learning in R
- Machine Learning in the Tidyverse
- Intermediate Regression in R
- Cluster Analysis in R
More about this course
- Learn how to process data for modeling, train your models, visualize your models and assess their performance, and tune their parameters for better performance
- Get an introduction to Bayesian statistics, natural language processing, and Spark
- Learn the basics of machine learning for classification
- Learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost
- This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective
- Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models
- Learn to perform linear and logistic regression with multiple explanatory variables
- Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data
Machine Learning Scientist with R at DataCamp Curriculum
Machine Learning Scientist with R
at DataCamp
Supervised Learning in R: Classification
Supervised Learning in R: Regression
Unsupervised Learning in R
Machine Learning in the Tidyverse
Intermediate Regression in R
Cluster Analysis in R
Machine Learning with caret in R
Modeling with tidymodels in R
Machine Learning with Tree-Based Models in R
Model Development with R
Support Vector Machines in R
Fundamentals of Bayesian Data Analysis in R
Topic Modeling in R
Hyperparameter Tuning in R
Bayesian Regression Modeling with rstanarm
Machine Learning Scientist with R at DataCamp Faculty details
Machine Learning Scientist with R
at DataCamp
Brett Lantz
Brett Lantz is a data scientist at the University of Michigan and the author of Machine Learning with R. After training as a sociologist, Brett has applied his endless thirst for data to projects that involve understanding and predicting human behavior.
John Mount
John is a co-founder and principal consultant at Win-Vector LLC, a San Francisco data science consultancy. He is the author of several R packages, including the data treatment package vtreat.
Nina Zumel
Nina is a co-founder and principal consultant at Win-Vector LLC, a San Francisco data science consultancy. She is co-author of the popular text Practical Data Science with R and occasionally blogs at the Win-Vector Blog on data science and R.
Hank Roark
Hank is a Senior Data Scientist at Boeing and a long time user of the R language. Prior to his current role, he led the Customer Data Science team at H2O.ai, a leading provider of machine learning and predictive analytics services.
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T
Thadaka Kalyan Chakravarthy
Machine Learning Scientist with R
5
Other: Machine Learning Scientist course is best to understand the ML algorithms, and also this course gives knowledge to write on own ML algorithms.
Reviewed on 12 Sep 2021Read More
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Machine Learning Scientist with R
at DataCamp
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